scholarly journals Digital Examination of Vegetation Changes in River Floodplain Wetlands Based on Remote Sensing Images: A Case Study Based on the Downstream Section of Hailar River

Forests ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1206
Author(s):  
Xi Dong ◽  
Zhibo Chen
Keyword(s):  
Remote Sensing ◽  
Water Supply ◽  
Plant Community ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Forest Vegetation ◽  
High Rate ◽  
Vegetation Changes ◽  
Herbaceous Plant ◽  
Sparse Vegetation

The Hailar River is an important river in the Inner Mongolia Autonomous Region, China. It plays an extremely important role in maintaining the ecological balance of the region. However, in recent decades, the Hailar River and its surrounding areas have been developed at a high rate and its wetland resources have faced various threats. In this study, vegetation changes in the Hailar River wetlands were analyzed using remote sensing data from the Landsat TM (1987, 2001, and 2010) and Landsat OLI-TIRS (2019) satellites. A vegetation change model was developed using Matlab software to assess vegetation changes in the area. There were significant changes in the wetland vegetation of the lower Hailar River study site between 1987 and 2019. There was an increase in open sand habitat with a sparse vegetation area of 1.08 km2, a decrease in grassland area of 13.17 km2, and an increase in the forest area of 15.91 km2. The spatial distribution of the normalized difference vegetation index (NDVI) varied across the study site and was high overall. The vegetation types varied with distance from the river. There are two possible explanations for positive and negative vegetation change trends. In areas where the water supply is sufficient and relatively stable, the cover of forest vegetation was gradually increasing and the herbaceous plant community is gradually evolving into a scrub woodland plant community. In areas where the water supply is lacking, there are changes in the sense of a decrease of forest vegetation and an increase of open sand habitat with sparse vegetation. Therefore, this study suggests that the existing wetlands should be protected, used wisely, and developed rationally to provide sustainable resources for the next generation.

scholarly journals Vegetation Dynamic Assessment by NDVI and Field Observations for Sustainability of China’s Wulagai River Basin

2021 ◽  
Vol 18 (5) ◽  
pp. 2528
Author(s):  
Panpan Chen ◽  
Huamin Liu ◽  
Zongming Wang ◽  
Dehua Mao ◽  
Cunzhu Liang ◽  
...  
Keyword(s):  
Species Diversity ◽  
River Basin ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Dynamic Assessment ◽  
Indicator System ◽  
Vegetation Changes ◽  
Vegetation Dynamic ◽  
Management Policies ◽  
The Impact

Accurate monitoring of grassland vegetation dynamics is essential for ecosystem restoration and the implementation of integrated management policies. A lack of information on vegetation changes in the Wulagai River Basin restricts regional development. Therefore, in this study, we integrated remote sensing, meteorological, and field plant community survey data in order to characterize vegetation and ecosystem changes from 1997 to 2018. The residual trend (RESTREND) method was utilized to detect vegetation changes caused by human factors, as well as to evaluate the impact of the management of pastures. Our results reveal that the normalized difference vegetation index (NDVI) of each examined ecosystem type showed an increasing trend, in which anthropogenic impact was the primary driving force of vegetation change. Our field survey confirmed that the meadow steppe ecosystem increased in species diversity and aboveground biomass; however, the typical steppe and riparian wet meadow ecosystems experienced species diversity and biomass degradation, therefore suggesting that an increase in NDVI may not directly reflect ecosystem improvement. Selecting an optimal indicator or indicator system is necessary in order to formulate reasonable grassland management policies for increasing the sustainability of grassland ecosystems.

scholarly journals Detecting Spatiotemporal Changes in Vegetation with the BFAST Model in the Qilian Mountain Region during 2000–2017

2019 ◽  
Vol 11 (2) ◽  
pp. 103 ◽  
Author(s):  
Liying Geng ◽  
Tao Che ◽  
Xufeng Wang ◽  
Haibo Wang
Keyword(s):  
Large Scale ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Anthropogenic Activities ◽  
Western China ◽  
Qinghai Lake ◽  
Vegetation Changes ◽  
Qilian Mountain ◽  
Modis Ndvi ◽  
Positive Effects

The Qilian Mountain ecosystems play an irreplaceable role in maintaining ecological security in western China. Vegetation, as an important part of the ecosystem, has undergone considerable changes in recent decades in this area, but few studies have focused on the process of vegetation change. A long normalized difference vegetation index (NDVI) time series dataset based on remote sensing is an effective tool to investigate large-scale vegetation change dynamics. The MODerate resolution Imaging Spectroradiometer (MODIS) NDVI dataset has provided very detailed regional to global information on the state of vegetation since 2000. The aim of this study was to explore the spatial-temporal characteristics of abrupt vegetation changes and detect their potential drivers in the Qilian Mountain area using MODIS NDVI data with 1 km resolution from 2000 to 2017. The Breaks for Additive Season and Trend (BFAST) algorithm was adopted to detect vegetation breakpoint change times and magnitudes from satellite observations. Our results indicated that approximately 80.1% of vegetation areas experienced at least one abrupt change from 2000 to 2017, and most of these areas were distributed in the southern and northern parts of the study area, especially the area surrounding Qinghai Lake. The abrupt browning changes were much more widespread than the abrupt greening changes for most years of the study period. Environmental factors and anthropogenic activities mainly drove the abrupt vegetation changes. Long-term overgrazing is likely the main cause of the abrupt browning changes. In addition, our results indicate that national ecological protection policies have achieved positive effects in the study area.

EFFECT OF INDIAN OCEAN CYCLONE ON COASTAL REGION USING REMOTE SENSING AND GIS

2020 ◽  
pp. 2050005
Author(s):  
KHUSHBOO KUMARI ◽  
ASMITA A. DEO
Keyword(s):  
Remote Sensing ◽  
Tamil Nadu ◽  
Andhra Pradesh ◽  
Vegetation Index ◽  
Coastal Region ◽  
Risk Zone ◽  
Sparse Vegetation ◽  
Dense Vegetation ◽  
Risk Zonation ◽  
Before And After

The effect of four different cyclones making land fall on four different coastal regions is studied viz., Nisha (2008, Tamil Nadu), Laila (2010, Andhra Pradesh), Sidr (2007, Bangladesh) and land depression BOB 03 (2008, Orissa). Remote sensing and Geographic Information System (GIS) technique are used to detect change in Land use and Land cover (LU/LC). Change in vegetation cover by Normalized Vegetation Index (NDVI) is also investigated. Further, preparation of slope map, processing of buffer zoning map is exercised. These parameters are analyzed to find the impression of cyclones after hitting the coastal boundaries by considering the images before and after the cyclone has passed. Change detection assessment of LU/LC features provides information for monitoring the trend of change in an area. In almost every considered region, it is found that dense vegetation is changed to sparse vegetation. Also, decrease in the irrigated cropland due to heavy rainfall caused by cyclone is noted. Risk zone is created by buffer ring of cyclone track to spot the area under risk zone. The area calculation suggests the effect of cyclone at the distance of 20–50[Formula: see text]km from the cyclone path which is validated from the slope effect on LU/LC, also. Some of the common features such as dense vegetation, show decrease in the area by 71%, 17%, 67% and 60%, or settlement area also shows decrease by 38%, 15%, 57% and 17% due to Laila, BOB 03, Nisha and Sidr cyclones, respectively. Increase in shrubland mix with rangeland by 18%, 113% and 98% is also seen due to Laila, Nisha and Sidr cyclones. Other LU/LC shows changes such as, water bodies increasing by 6%, 189% due to BOB 03 and Nisha cyclones. Changes are also seen in sparsed vegetation, which is decreased in Orissa and Tamil Nadu and increased in Andhra Pradesh and Bangladesh. It is demonstrated that by preparing risk zonation map, risk assessment can be done.

Greening dynamics and shrubland extent from remote sensing data using NDVI and NARI Indices: case study of the George River basin (Nunavik, Canada).

2020 ◽  
Author(s):  
Dr. Jean-Pierre Dedieu ◽  
Johann Housset ◽  
Arthur Bayle ◽  
Esther Lévesque ◽  
José Gérin-Lajoie
Keyword(s):  
Remote Sensing ◽  
River Basin ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Spectral Band ◽  
Human Populations ◽  
Vegetation Types ◽  
Local Study ◽  
Basin Scale ◽  
George River

<p>Arctic greening trends are well documented at various scales (Fraser et al., 2011; Tremblay et al., 2012; Bjorkman et al., 2018). In this context, Remote Sensing offers a unique tool for estimating the high latitude vegetation evolution in the relatively long-term, i.e. the Landsat archive since the 80’s. Spectral indices derived from visible and infra-red wavelengths provide relations that can be used to quantify vegetation dynamics, we will combine the well-used Normalized Difference Vegetation Index (NDVI) and the recent Normalized Anthocyanins Reflectance Index (Bayle et al., 2019), using red-edge spectral band (690 to 710 µm) from Sentinel-2, to better quantify vegetation change over 30 years.</p><p>The application area is located in Nunavik, northern Québec (Canada), and concerns the George River catchment (565 km length, 41 700 km²). This large river basin covers vegetation from boreal forest (South) to arctic tundra (North). Local study sites stem from the Kangiqsualujjuaq village (Ungava Bay) to 300 km south, along the main river and its tributaries.</p><p>NDVI: surface reflectance Landsat bands were gathered for three years 1985, 2000 and 2015 (respectively Landsat missions 5, 7 and 8). For each period of interest, the best August cloud-free scenes were chosen and merged to create a cloud free mosaic covering the study area. NDVI bands were calculated and compared after cloud and water masking. NDVI trends were compared between the main vegetation types following the newly released “Ecological mapping of the vegetation of northern Quebec” (MRNFP, 2018). Centroid of polygons within the main vegetation types of the map were used to classify the NDVI results and assess changes per type. Results of NDVI time evolution revealed a clear greening trend at the river basin scale. Although greening was observed across the whole latitudinal gradient, the relative NDVI increase was stronger on the northern half of the study area, mostly covered with tundra and subarctic vegetation. Both shrublands and sparsely vegetated zones dominated by rocks had the greatest relative NDVI increase. This is likely caused by improved growth of established prostrate vegetation over the past 30 years in response to increasing temperatures trend.</p><p>NARI: greening trends in the Eastern Canadian Arctic have been partly attributed to increases in shrub cover (Myers-smith et al., 2011) and specifically to Betula glandulosa (e.g. Tremblay et al., 2012). Such land cover changes alter species competition (Shevtosa et al., 1997) and soil thermal regime (Domine et al., 2015; Paradis et al., 2016). Transformations in biotic and abiotic conditions reduce the fruit productivity of low stature shrubs of the Ericaceae family (Lussier 2017), which in turn is expected to impact animal (Prescott and Richard 2013) and human populations (Lévesque et al., 2013; Boulanger-Lapointe et al., 2019). An innovative method has been developed in the French Alps to detect the late-fall reddening of shrub leaves and map shrublands (Bayle et al., 2019). Quantifying NARI dynamics related to NDVI dynamics could allow to gain a better understanding of species composition change related to current landscape transformation.</p>

scholarly journals Mapeamento e Quantificação da Cobertura Vegetal no Agreste Central de Pernambuco Utilizando Técnicas de Empilhamento e o NDVI (Mapping and Quantification of Vegetation Cover from Central Agreste Region of Pernambuco State Using NDVI Technique)

2011 ◽  
Vol 3 (3) ◽  
pp. 157
Author(s):  
Daniel Rodrigues Lira ◽  
Maria do Socorro Bezerra de Araújo ◽  
Everardo Valadares De Sá Barretto Sampaio ◽  
Hewerton Alves da Silva
Keyword(s):  
Remote Sensing ◽  
Vegetation Cover ◽  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Regional Scale ◽  
Digital Processing ◽  
Sparse Vegetation ◽  
New Sensors

O mapeamento e monitoramento da cobertura vegetal receberam consideráveis impulsos nas últimas décadas, com o advento do sensoriamento remoto, processamento digital de imagens e políticas de combate ao desmatamento, além dos avanços nas pesquisas e gerações de novos sensores orbitais e sua distribuição de forma mais acessível aos usuários, tornam as imagens de satélite um dos produtos do sensoriamento remoto mais utilizado para análises da cobertura vegetal das terras. Os índices de cobertura vegetal deste trabalho foram obtidos usando o NDVI - Normalized Difference Vegetation Index para o Agreste central de Pernambuco indicou 39,7% de vegetação densa, 13,6% de vegetação esparsa, 14,3% de vegetação rala e 10,5% de solo exposto. O NDVI apresentou uma caracterização satisfatória para a classificação do estado da vegetação do ano de 2007 para o Agreste Central pernambucano, porém ocorreu uma confusão com os índices de nuvens, sombras e solos exposto, necessitando de uma adaptação na técnica para um melhor aprimoramento da diferenciação desses elementos, constituindo numa recombinação de bandas após a elaboração e calculo do NDVI.Palavras-chave: Geoprocessamento; sensoriamento remoto; índice de vegetação. Mapping and Quantification of Vegetation Cover from Central Agreste Region of Pernambuco State Using NDVI Technique ABSTRACTIn recent decades, advanced techniques for mapping and monitoring vegetation cover have been developed with the advent of remote sensing. New tools for digital processing, the generation of new sensors and their orbital distribution more accessible have facilitated the acquisition and use of satellite images, making them one of the products of remote sensing more used for analysis of the vegetation cover. The aim of this study was to assess the vegetation cover from Central Agreste region of Pernambuco State, using satellite images TM / LANDSAT-5. The images were processed using the NDVI (Normalized Difference Vegetation Index) technique, generating indexes used for classification of vegetation in dense, sparse and scattered. There was a proportion of 39.7% of dense vegetation, 13.6% of sparse vegetation, 14.3% of scattered vegetation and 10.5% of exposed soil. NDVI technique has been used as a useful tool in the classification of vegetation on a regional scale, however, needs improvement to a more precise differentiation among levels of clouds, shadow, exposed soils and vegetation. Keywords: Geoprocessing, remote sensing, vegetation index

Forest Vegetation Spatial and Temporal Pattern Analysis Based on NDVI in Jiuzhaigou

2014 ◽  
Vol 675-677 ◽  
pp. 1163-1170
Author(s):  
Yi Shu Qiu ◽  
Jun Gao ◽  
Qi Lin Zhan
Keyword(s):  
Remote Sensing ◽  
Temporal Pattern ◽  
Vegetation Index ◽  
Pattern Analysis ◽  
Image Data ◽  
Forest Vegetation ◽  
Spatial And Temporal Variation ◽  
Remote Sensing Images ◽  
Analysis Process ◽  
Spatial And Temporal Characteristics

This paper takes Jiuzhaigou area for example, selecting Landsat remote sensing images in phase time about years of 1999, 2002, 2006 and 2007, using ENVI and ArcGIS software for image data processing, making spatial and temporal characteristics and distribution pattern analysis of vegetation index NDVI of Jiuzhaigou forest. The result shows that NDVI of Jiuzhaigou forest has obvious characteristics of spatial and temporal variation. The paper provides the analysis process and reference to the forest vegetation research of other areas.

scholarly journals Exploring Life Forms for Linking Orthopteran Assemblage and Grassland Plant Community

Hacquetia ◽  
2015 ◽  
Vol 14 (1) ◽  
pp. 33-42 ◽  
Author(s):  
Rocco Labadessa ◽  
Luigi Forte ◽  
Paola Mairota
Keyword(s):  
Plant Community ◽  
Plant Communities ◽  
Vegetation Change ◽  
Relative Proportion ◽  
Life Forms ◽  
Herbaceous Plant ◽  
Community Patterns ◽  
Plant Life Forms ◽  
Grassland Conservation ◽  
Biodiversity Changes

AbstractOrthopterans are well known to represent the majority of insect biomass in many grassland ecosystems. However, the verification of a relationship between the traditional descriptors of orthopteran assemblage structure and plant community patterns is not straightforward. We explore the usefulness of the concept of life forms to provide insights on such ecosystem level relationship. For this purpose, thirty sample sites in semi-natural calcareous grasslands were classified according to the relative proportion of dominant herbaceous plant life forms. Orthopteran species were grouped in four categories, based on the Bei-Bienko’s life form categorization. The association among plant communities, orthopteran assemblages and environmental factors was tested by means of canonical correspondence analysis. Orthoptera groups were found to be associated with distinct plant communities, also indicating the effect of vegetation change on orthopteran assemblages. In particular, geobionta species were associated with all the most disturbed plant communities, while chortobionta and thamnobionta seemed to be dependent on better preserved grassland types. Therefore, the use of life forms could help informing on the relationships of orthopteran assemblages with grassland conservation state. Information on such community relationships at the local scale could also assist managers in the interpretation of habitat change maps in terms of biodiversity changes.

scholarly journals Topographic Controls on Vegetation Changes in Alpine Tundra of the Changbai Mountains

Forests ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 756 ◽  
Author(s):  
Miaomiao Wu ◽  
Hong He ◽  
Shengwei Zong ◽  
Xinyuan Tan ◽  
Haibo Du ◽  
...  
Keyword(s):  
High Altitude ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Scale Effects ◽  
Alpine Tundra ◽  
Changbai Mountains ◽  
Vegetation Changes ◽  
Tundra Vegetation ◽  
Topographic Controls ◽  
Low Altitude

The vegetation of alpine tundra is undergoing significant changes and topography has played a significant role in mediating such changes. The roles of topography varied at different scales. In this study, we intended to identify topographic controls on tundra vegetation changes within the Changbai Mountains of Northeast China and reveal the scale effects. We delineated the vegetation changes of the last three decades using the normalized difference vegetation index (NDVI) time series. We conducted a trend analysis for each pixel to reveal the spatial change and used binary logistic regression models to analyze the relationship between topographic controls at different scales and vegetation changes. Results showed that about 30% of tundra vegetation experienced a significant (p < 0.05) change in the NDVI, with 21.3% attributable to the encroachment of low-altitude plants resulting in a decrease in the NDVI, and 8.7% attributable to the expansion of tundra endemic plants resulting in an increase in the NDVI. Plant encroachment occurred more severely in low altitude than in high altitude, whereas plant expansion mostly occurred near volcanic ash fields at high altitude. We found that plant encroachment tended to occur in complex terrains and the broad-scale mountain aspect had a greater effect on plant encroachment than the fine-scale local aspect. Our results suggest that it is important to include the mountain aspect in mountain vegetation change studies, as most such studies only use the local aspect.

scholarly journals Changes in Vegetation on Mount Agung Volcano Bali Indonesia

2019 ◽  
Vol 4 (2) ◽  
pp. 54
Author(s):  
Sutomo Sutomo ◽  
Luthfi Wahab
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Present Condition ◽  
Short Time Scale ◽  
Landsat 8 ◽  
Web Based ◽  
Volcanic Event ◽  
The Past

Volcanic activity is a major natural disturbance that can catastrophically change an ecosystem over a short time scale. The eruption of Mt. Agung strato-volcano in 1963-1964 was considered among the most important volcanic event of the 20th century due to its effect on global climate. Studies on vegetation and landscape of Mt. Agung post-1970-1980 has been scarce. The current eruption of Mount Agung in June-July 2018, brought awareness of the importance urge to document the past and current landscape along with vegetation on Mt. Agung. Our study aimed to utilize remote sensing technique to explore the pattern of current (2017) land cover and vegetation density on Mt. Agung and estimate of vegetated areas and whether it has changed from the past. LANDSAT 8 images (www.earthexplorer.usgs.gov/) were used in this study. Supervised classification in ENVI was employed to obtain land use or land cover of the Mt. Agung area. Normalized Difference Vegetation Index (NDVI) was also calculated using the feature in the ARC GIS. Online web-based application, REMAP was used to obtain information on past and present condition of the crater of Mt. Agung to see whether there have been changes in vegetated areas around the crater using REMAP (www.remap-app.org). Results showed there are basically five main landcover that can be recognized namely forest (20758.23 ha), settlement (4058.37 ha), water area (41606.64 ha), open area (15335.64 ha) and farming (34554.78 ha). Our NDVI analysis also resulted in areas with have high density (78836.04 ha), medium density (15490.26 ha) and also no vegetation (31008.24 ha). Using web-based GIS application REMAP, we found that there has been an increase (approximately 1 km2) in vegetation cover from the 1980s to 2016.  The changes in vegetation near the crater of Mt. Agung is relatively slow when compared to another volcano such as Mt. Merapi. Remote sensing application has enabled us to obtain information on vegetation change relatively easily compared to conduct an extensive on-ground survey where more time and funding is needed.

scholarly journals Using Hyperspectral Imagery to Characterize Rangeland Vegetation Composition at Process-Relevant Scales

2021 ◽  
Vol 13 (22) ◽  
pp. 4603
Author(s):  
Rowan Gaffney ◽  
David J. Augustine ◽  
Sean P. Kearney ◽  
Lauren M. Porensky
Keyword(s):  
Plant Community ◽  
Plant Communities ◽  
Vegetation Change ◽  
Spatial Scales ◽  
Hyperspectral Data ◽  
Rangeland Management ◽  
Herbaceous Plant ◽  
Complex Data ◽  
Vegetation Composition ◽  
Management Regime

Rangelands are composed of patchy, highly dynamic herbaceous plant communities that are difficult to quantify across broad spatial extents at resolutions relevant to their characteristic spatial scales. Furthermore, differentiation of these plant communities using remotely sensed observations is complicated by their similar spectral absorption profiles. To better quantify the impacts of land management and weather variability on rangeland vegetation change, we analyzed high resolution hyperspectral data produced by the National Ecological Observatory Network (NEON) at a 6500-ha experimental station (Central Plains Experimental Range) to map vegetation composition and change over a 5-year timescale. The spatial resolution (1 m) of the data was able to resolve the plant community type at a suitable scale and the information-rich spectral resolution (426 bands) was able to differentiate closely related plant community classes. The resulting plant community class map showed strong accuracy results from both formal quantitative measurements (F1 75% and Kappa 0.83) and informal qualitative assessments. Over a 5-year period, we found that plant community composition was impacted more strongly by weather than by the rangeland management regime. Our work displays the potential to map plant community classes across extensive areas of herbaceous vegetation and use resultant maps to inform rangeland ecology and management. Critical to the success of the research was the development of computational methods that allowed us to implement efficient and flexible analyses on the large and complex data.

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