Multiple Effects of Topographic Factors on Spatio-temporal Variations of Vegetation Patterns in the Three Parallel Rivers Region, Southeast Tibet

2021 ◽  
Author(s):  
Chunya Wang ◽  
Jinniu Wang ◽  
Niyati Naudiyal ◽  
Ning Wu ◽  
Xia Cui ◽  
...  
Keyword(s):  
River Basin ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Vegetation Type ◽  
Temporal Variations ◽  
Vegetation Patterns ◽  
Jinsha River ◽  
Modis Ndvi ◽  
Topographic Factors ◽  
Significant Difference

Topographic factors are recognized as one of the key factors influencing vegetation distribution patterns, and studying the interactions between them can contribute to enhancing our understanding of future vegetation dynamics. We used the Moderate-resolution Imaging Spectroradiometer Normalized Differential Vegetation Index (MODIS NDVI) image dataset (2000-2019), combined with Digital Elevation Model (DEM), and vegetation type data for trend analysis, and explored NDVI variation and its relationship with topographic factors through an integrated geographically-weighted model in the Three Parallel Rivers Region (TPRR) of southeastern Tibetan plateau in the past 20 years. Our results indicated that there was no significant increase of NDVI in the entire basin between 2000-2019, except for the Lancang River basin. In the year 2004, abrupt changes in NDVI were observed across the whole basin and each sub-basin. During 2000-2019, the mean NDVI value of the whole basin increased initially and then decreased with the increasing elevation. However, it changed marginally with changes in slope and aspect. We observed a distinct spatial heterogeneity in vegetation patterns with elevation, with vegetation in the southern regions showing higher NDVI than the north as a whole. Most of the vegetation cover was concentrated in the slope range of 8~35°, with no significant difference in distribution except flat-land. Furthermore, from 2000 to 2019, the vegetation cover in the TPRR showed an improving trend with the changes of various topographic factors, with the largest improvement area (36.10%) in the slightly improved category. The improved region was mainly distributed in the source area of the Jinsha River basin and the southern part of the whole basin. Geographically weighted regression (GWR) analysis showed that elevation was negatively correlated with NDVI trends in most areas, especially in the middle reaches of Nujiang River basin and Jinsha River basin, where the influence of slope and aspect on NDVI change was considerably much smaller than elevation.

scholarly journals Multiple Effects of Topographic Factors on Spatio-temporal Variations of Vegetation Patterns in the Three Parallel Rivers Region, Southeast Tibet

2021 ◽  
Author(s):  
Chunya Wang ◽  
Jinniu Wang ◽  
Niyati Naudiyal ◽  
Ning Wu ◽  
Xia Cui ◽  
...  
Keyword(s):  
River Basin ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Vegetation Type ◽  
Temporal Variations ◽  
Vegetation Patterns ◽  
Jinsha River ◽  
Modis Ndvi ◽  
Topographic Factors ◽  
Significant Difference

Topographic factors are recognized as one of the key factors influencing vegetation distribution patterns, and studying the interactions between them can contribute to enhancing our understanding of future vegetation dynamics. We used the Moderate-resolution Imaging Spectroradiometer Normalized Differential Vegetation Index (MODIS NDVI) image dataset (2000-2019), combined with Digital Elevation Model (DEM), and vegetation type data for trend analysis, and explored NDVI variation and its relationship with topographic factors through an integrated geographically-weighted model in the Three Parallel Rivers Region (TPRR) of southeastern Tibetan plateau in the past 20 years. Our results indicated that there was no significant increase of NDVI in the entire basin between 2000-2019, except for the Lancang River basin. In the year 2004, abrupt changes in NDVI were observed across the whole basin and each sub-basin. During 2000-2019, the mean NDVI value of the whole basin increased initially and then decreased with the increasing elevation. However, it changed marginally with changes in slope and aspect. We observed a distinct spatial heterogeneity in vegetation patterns with elevation, with vegetation in the southern regions showing higher NDVI than the north as a whole. Most of the vegetation cover was concentrated in the slope range of 8~35°, with no significant difference in distribution except flat-land. Furthermore, from 2000 to 2019, the vegetation cover in the TPRR showed an improving trend with the changes of various topographic factors, with the largest improvement area (36.10%) in the slightly improved category. The improved region was mainly distributed in the source area of the Jinsha River basin and the southern part of the whole basin. Geographically weighted regression (GWR) analysis showed that elevation was negatively correlated with NDVI trends in most areas, especially in the middle reaches of Nujiang River basin and Jinsha River basin, where the influence of slope and aspect on NDVI change was considerably much smaller than elevation.

scholarly journals Multiple Effects of Topographic Factors on Spatio-Temporal Variations of Vegetation Patterns in the Three Parallel Rivers Region, Southeast Qinghai-Tibet Plateau

2021 ◽  
Vol 14 (1) ◽  
pp. 151
Author(s):  
Chunya Wang ◽  
Jinniu Wang ◽  
Niyati Naudiyal ◽  
Ning Wu ◽  
Xia Cui ◽  
...  
Keyword(s):  
River Basin ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Vegetation Type ◽  
Tibet Plateau ◽  
Vegetation Patterns ◽  
Jinsha River ◽  
Topographic Factors ◽  
Significant Difference ◽  
Qinghai Tibet Plateau

Topographic factors are critical for influencing vegetation distribution patterns, and studying the interactions between them can enhance our understanding of future vegetation dynamics. We used the Moderate-resolution Imaging Spectroradiometer Normalized Differential Vegetation Index (MODIS NDVI) image dataset (2000–2019), combined with the Digital Elevation Model (DEM), and vegetation type data for trend analysis, and explored NDVI variation and its relationship with topographic factors through an integrated geographically-weighted model in the Three Parallel Rivers Region (TPRR) of southeastern Qinghai-Tibet Plateau (QTP) in the past 20 years. Our results indicated that there was no significant increase of NDVI in the entire basin between 2000–2019, except for the Lancang River basin. In the year 2004, abrupt changes in NDVI were observed across the entire basin and each sub-basin. During 2000–2019, the mean NDVI value of the whole basin increased initially and then decreased with the increasing elevation. However, it changed marginally with variations in slope and aspect. We observed a distinct spatial heterogeneity in vegetation patterns with elevation, with higher NDVI in the southern regions NDVI than those in the north as a whole. Most of the vegetation cover was concentrated in the slope range of 8~35°, with no significant difference in distribution except flat land. Furthermore, from 2000 to 2019, the vegetation cover in the TPRR showed an improving trend with the changes of various topographic factors, with the largest improvement area (36.10%) in the slightly improved category. The improved region was mainly distributed in the source area of the Jinsha River basin and the southern part of the whole basin. Geographically weighted regression (GWR) analysis showed that elevation was negatively correlated with NDVI trends in most areas, especially in the middle reaches of Nujiang River basin and Jinsha River basin, where the influence of slope and aspect on NDVI change was considerably much smaller than elevation. Our results confirmed the importance of topographic factors on vegetation growth processes and have implications for understanding the sustainable development of mountain ecosystems.

The spatio-temporal variations of vegetation cover in the Yellow River Basin from 2000 to 2010

2013 ◽  
Vol 33 (24) ◽  
Author(s):  
袁丽华 YUAN Lihua ◽  
蒋卫国 JIANG Weiguo ◽  
申文明 SHEN Wenming ◽  
刘颖慧 LIU Yinghui ◽  
王文杰 WANG Wenjie ◽  
...  
Keyword(s):  
River Basin ◽  
Vegetation Cover ◽  
Yellow River ◽  
Yellow River Basin ◽  
Temporal Variations ◽  
The Yellow River ◽  
Spatio Temporal ◽  
The Yellow River Basin

scholarly journals Temporal Influences of Vegetation Cover (C) Dynamism on MUSLE Sediment Yield Estimates: NDVI Evaluation

Water ◽  
2021 ◽  
Vol 13 (19) ◽  
pp. 2707
Author(s):  
David Gwapedza ◽  
Denis Arthur Hughes ◽  
Andrew Robert Slaughter ◽  
Sukhmani Kaur Mantel
Keyword(s):  
Sediment Yield ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Scale Validation ◽  
Spatial Scales ◽  
Temporal Variations ◽  
Early Summer ◽  
Landsat 8 ◽  
Temporal Scales ◽  
Normalised Difference Vegetation Index

Vegetation cover is an important factor controlling erosion and sediment yield. Therefore, its effect is accounted for in both experimental and modelling studies of erosion and sediment yield. Numerous studies have been conducted to account for the effects of vegetation cover on erosion across spatial scales; however, little has been conducted across temporal scales. This study investigates changes in vegetation cover across multiple temporal scales in Eastern Cape, South Africa and how this affects erosion and sediment yield modelling in the Tsitsa River catchment. Earth observation analysis and sediment yield modelling are integrated within this study. Landsat 8 imagery was processed, and Normalised Difference Vegetation Index (NDVI) values were extracted and applied to parameterise the Modified Universal Soil Loss Equation (MUSLE) vegetation (C) factor. Imagery data from 2013–2018 were analysed for an inter-annual trend based on reference summer (March) images, while monthly imagery for the years 2016–2017 was analysed for intra-annual trends. The results indicate that the C exhibits more variation across the monthly timescale than the yearly timescale. Therefore, using a single month to represent the annual C factor increases uncertainty. The modelling shows that accounting for temporal variations in vegetation cover reduces cumulative simulated sediment by up to 85% across the inter-annual and 30% for the intra-annual scale. Validation with observed data confirmed that accounting for temporal variations brought cumulative sediment outputs closer to observations. Over-simulations are high in late autumn and early summer, when estimated C values are high. Accordingly, uncertainties are high in winter when low NDVI leads to high C, whereas dry organic matter provides some protection from erosion. The results of this study highlight the need to account for temporal variations in vegetation cover in sediment yield estimation but indicate the uncertainties associated with using NDVI to estimate C factor.

scholarly journals Spatial-Temporal variations of vegetation and the relationship with precipitation in summer-A case study in the hilly area of central Sichuan province

2018 ◽  
Vol 53 ◽  
pp. 03060
Author(s):  
Xinrui Luo ◽  
Wunian Yang ◽  
Liang Liu ◽  
Yuhang Zhang
Keyword(s):  
Climate Change ◽  
Vegetation Cover ◽  
Yangtze River ◽  
Ecological Engineering ◽  
Temporal Variations ◽  
The Yangtze River ◽  
Climate Data ◽  
Modis Ndvi ◽  
Hilly Area ◽  
Vegetation Cover Change

The hilly area of central Sichuan is one of the ecologically fragile regions in the upper reaches of the Yangtze River, and it is also the main part of ecological engineering construction. The ecological environment in the study area is related to the ecological security in the middle and lower reaches of the Yangtze River. Recent years have witnessed a great change in vegetation cover in this area as a result of climate change. Therefore, it is necessary to identify the changing patterns of vegetation cover and the impacts of climate change on the vegetation cover change in the study area. In this paper, the characteristics of vegetation cover change over the past 15 years were analyzed, based on the dataset of MODIS NDVI from 2001 to 2015 as well as the climate data from 55 meteorological stations, with methods such as maximum value composite (MVC), linear regression and correlation coefficient. The results showed that the annual maximum average NDVI in the hilly areas of central Sichuan has increased at a rate of 5.84/10a (P<0.01), while the summer average NDVI has increased at a rate of 1.6/10a (P>0.1). The spatial distribution of annual NDVI significantly increased (31.58%) was greater than the significantly decreasing trend (2.90%). Besides, areas with significantly positive correlation and significantly negative correlation between NDVI and precipitation in summer accounted for 16.91% and 2.5% of the total area, respectively. And, the correlation between NDVI and precipitation in summer was different in different regions.

scholarly journals Impact of rural depopulation and climate change on vegetation, runoff and sediment load in the Gan River basin, China

2020 ◽  
Vol 51 (4) ◽  
pp. 768-780
Author(s):  
Lidong Huang ◽  
Aizhong Ye ◽  
Chongjun Tang ◽  
Qingyun Duan ◽  
Yahai Zhang
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Rural Population ◽  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Temporal Variations ◽  
Farmland Abandonment ◽  
Causality Test ◽  
Rural Depopulation

Abstract Climate change and rural depopulation are changing the ecological and hydrological cycles in China. Data on the normalized difference vegetation index (NDVI), temperature, precipitation, streamflow, sediment and rural population are available for the Gan River basin from 1981 to 2017. We investigated the spatio-temporal variations in climate, human activity and vegetation mainly using the Mann–Kendall test and examined their relationship using the Granger causality test. The results showed that (1) the temperature markedly increased in all seasons; (2) the precipitation increased in summer and winter but decreased in spring and autumn; (3) overall, the NDVI increased markedly during 2005–2017, but showed seasonal differences, with decreases in summer and winter and increases in spring and autumn; (4) the annual sediment transport showed a significant decreasing trend and (5) a large number of the population shifted from rural to urban areas, resulting in a decrease in the rural population between 1998 and 2018. Rural depopulation has brought about farmland abandonment, conversion of farmland to forests, which was the factor driving the recovery of the vegetation and the decrease in sediment. The results of this study can provide support for climate change adaptation and sustainable development.

scholarly journals Impacts of tropical hurricanes on the vegetation cover of the lower basin and estuary of San José del Cabo, Baja California Sur, Mexico

2020 ◽  
Vol 27 (1) ◽  
pp. 165-180
Author(s):  
Marcos Shiba-Reyes ◽  
◽  
Enrique Troyo ◽  
Raúl Martínez-Rincón ◽  
Aurora Breceda ◽  
...  
Keyword(s):  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Type ◽  
Stability Loss ◽  
San Jose ◽  
Landsat Images ◽  
Precipitation Decrease ◽  
One Year ◽  
The Impact

Introduction: Tropical hurricanes modify composition and structure of ecosystems. Objective: To analyze the impact of tropical hurricanes on the recovery and resilience of vegetation cover.Materials and methods: The resilience of the lower basin and estuary of San Jose del Cabo was evaluated by studying the impact of 11 tropical hurricanes (2013-2017) on the vegetation cover. Landsat images were analyzed for each event and two SPOT-6 images for the Hurricane Lidia. The areas of gain, stability, loss and recovery of vegetation types were estimated based on the analysis of changes in the Normalized Difference Vegetation Index (NDVI).Results and discussion: Average stability of vegetation cover was 90 %; however, in the case of hurricane Odile (2014) and Lidia (2017), stability decreased considerably, with a loss of 35.4 and 20.5 %, respectively, being the perennial herbaceous vegetation the most affected. One year after Odile and Lidia, recovery was 8.4 % and 25.4 %, respectively; the most recovered vegetation type was reed-tree. The analysis of SPOT-6 images allowed the detailed observation of Lidia's effect on palm grove. The main cause of its loss was runoff from the stream, which favored the growth of invasive species (Arundo donax L. and Tamarix sp.); furthermore, it was estimated that 1.4 ha were deforested, and an area of 20 ha affected by fire in 2017.Conclusion: Vegetation is resilient to tropical hurricanes; however, events that provide more than 50 % of annual precipitation decrease the capacity of vegetation to recover.

scholarly journals Temporal variations on NDVI predict temporal changes in vegetation cover across Patagonian drylands (Argentina)

Ecosistemas ◽  
2021 ◽  
Vol 30 (3) ◽  
pp. 2229
Author(s):  
Juan Gaitan ◽  
Nicolas Ciano ◽  
Gabriel Oliva ◽  
Donaldo Bran ◽  
Lucas Butti ◽  
...  
Keyword(s):  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Temporal Variations ◽  
Temporal Changes ◽  
Toma De Decisiones

La variación temporal del índice NDVI predice los cambios temporales de la cobertura vegetal en las tierras secas de la Patagonia argentina. En las tierras secas, la vegetación natural es una fuente importante de sustento para las comunidades que viven en ellas, dado que la utilizan como alimento, combustible y forraje para el ganado. Además de los bienes y servicios que brinda a las comunidades, la vegetación de las tierras secas también juega un papel importante en muchos procesos ecosistémicos, como por ejemplo el reciclaje de nutrientes o la protección del suelo frente a la erosión. Por lo tanto, el monitoreo a largo plazo de la cobertura vegetal es clave para la toma de decisiones en la gestión de estas regiones. En este estudio, analizamos la variación de la cobertura vegetal en 239 sitios de una red de monitoreo a largo plazo (red MARAS), en uno de los biomas de tierras secas más grandes del mundo: la estepa patagónica argentina. A continuación, la relacionamos con la variación de diferentes períodos del Índice de Vegetación de Diferencia Normalizada (Normalized Difference Vegetation Index, NDVI), obtenido del sensor MODIS, que sirve como variable predictora. El modelo empírico ajustado explicó hasta un 40% de la variación en la cobertura vegetal medida a campo. Con este sencillo modelo empírico hemos estimado y cartografiado los cambios temporales en la cobertura vegetal de un extenso bioma de tierras secas a bajo coste.

scholarly journals Analysing the effect of land use and vegetation cover on soil infiltration in three contrasting environments in northeast Spain

2017 ◽  
Vol 43 (1) ◽  
pp. 141 ◽  
Author(s):  
D. Regüés ◽  
D. Badía ◽  
M.T. Echeverría ◽  
M. Gispert ◽  
N. Lana-Renault ◽  
...  
Keyword(s):  
Land Use ◽  
Soil Moisture ◽  
Vegetation Cover ◽  
Vegetation Type ◽  
Temporal Variations ◽  
Joint Analysis ◽  
Soil Infiltration ◽  
Ebro Valley ◽  
Double Ring ◽  
Wide Range

This study presents a joint analysis of the information from 195 field infiltration experiments, using double ring devices. The experiments were carried out in 20 contrasting types of land use, distributed across three geographic contexts (coast of NE Catalonia, low mountains in the central Ebro Valley and mid-height mountains from the southern range of the Central Pyrenees). The objective of this research was to determine the most important factors explaining infiltration variability: land use, type of vegetation cover, soil and bedrock characteristics, soil moisture and altitude. Data analysis was performed by comparing variables using statistical methods: bivariate lineal correlation, ANOVA and Bonferroni multiple comparison tests. Results show that infiltration variability is the most important factor and mainly linked to land use, followed by vegetation type. In contrast, soil moisture did not show any relation with infiltration. The interpretation of these results suggests that the characteristics of the study areas are more decisive than temporal variations of soil water content, although humidity can influence land use to a greater or lesser degree. The validity of the results obtained in this study is supported by the wide range of land use and land cover analysed, located in areas with different geographical and geological characteristics.

scholarly journals Monitoring Vegetation Patterns at the Syrdarya River Basin from 2000 to 2015 using MODIS Data

2021 ◽  
pp. 27-36
Author(s):  
K. Samarkhanov ◽  
J. Abuduwaili ◽  
T. Ahmed
Keyword(s):  
Surface Temperature ◽  
River Basin ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Climatic Factors ◽  
Seasonal Temperature ◽  
Cropland Area

The dependence of vegetation condition dynamics as expressed by Normalized Difference Vegetation Index (NDVI) from hydro-climatic factors (Multiyear precipitation, land surface temperature) in the Syrdarya River Basin (SRB) was analyzed for the period of 16 years from 2000 to 2015. The analysis demonstrated a different correlation between NDVI and hydrometric parameters. According to experimental analyses, the average NDVI values reached a maximum in April and minimum in October, while the annual average values of land surface temperature were observed maximum in June and minimum in October. Correlation between precipitation and NDVI was positive and extraordinarily strong in Spring while the correlation between Land Surface Temperature (LST) and NDVI was found negative and strong. Correlation between LST and NDVI changed from positive in spring to negative in summer due to an increase in seasonal temperature and found a decrease of vegetation cover throughout the Syrdarya river basin. Desert vegetation area in plain part of SRB decreased while NDVI of cropland area in Syrdarya and Shu river basins remained the same or increased. Hydro-climatic factors negatively affected a decrease in vegetation cover, which leads to desertification processes.

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