scholarly journals Quantifying the Relative Contribution of the Climate Change and Human Activity on Runoff in the Choshui River Alluvial Fan, Taiwan

Land ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 825
Author(s):  
Hsin-Yu Chen ◽  
Chia-Chi Huang ◽  
Hsin-Fu Yeh
Keyword(s):  
Human Activities ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Hydrological Cycle ◽  
Alluvial Fan ◽  
Climate Factors ◽  
Simple Method ◽  
Important Indicator ◽  
Runoff Changes ◽  
The Impact

Climate factors and human activities are the leading causes of changes in the hydrological cycle. In addition to being an important part of the hydrological cycle, runoff is also an important indicator for assessing the amount of available water. Therefore, it is necessary to explore the reasons that have caused changes in runoff. In this study, the causes of runoff changes in the alluvial fan of the Choshui River from 1980–2018 are explored. Two simple methods, including a decomposition method based on the Budyko structure and a method based on climate elasticity, for which the necessary data are easy to obtain, are used to quantify the impact of climate factors and human activities on runoff changes. The results show that the runoff in the long term shows a significant transition point in 2003, where climate factors have contributed more than 90% of the change, while the influence of human activities on the changes in runoff appears to be relatively small. Moreover, the Budyko method and the Normalized Difference Vegetation Index (NDVI) show that the vegetation cover has decreased. In addition to providing a simple method to assess the causes of changes in runoff, this study also analyzes the causes of changes in the runoff of the alluvial fan of the Choshui River to provide a reference for water resource policy and land use management.

scholarly journals An Assessment of Human versus Climatic Impacts on Jing River Basin, Loess Plateau, China

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Yi He ◽  
Fei Wang ◽  
Xingmin Mu ◽  
Huiting Yan ◽  
Guangju Zhao
Keyword(s):  
Loess Plateau ◽  
Human Activities ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Sediment Load ◽  
Similar Process ◽  
Monthly Data ◽  
Climatic Impacts ◽  
The Impact ◽  
Linear Correlations

The impacts of climate change and human activities on runoff and sediment load are too integrated to distinguish their own contributions. We develop a new method to assess the impact of human activities based on paired years with similar precipitation and evapotranspiration (ET0) conditions (SPEC) using a 55-year monthly data of climate, runoff, and sediment load in 1958–2012 at Zhangjiashan Hydrologic Station of Jing River, Loess Plateau, China. The SPEC of paired periods is defined by similar annual amounts (difference less than 2.0%) and similar process (linear correlations of monthly data less than 0.05) which could set a precondition fixing the possible influence of climate factors. The runoff declined in all nine paired years, but the sediment load and concentration decreased in seven (78%) and six (67%) paired years, respectively. The further analysis with available data of land use and land cover (LUC), Normalized Difference Vegetation Index (NDVI), and soil and water measures in this basin and the results could explain impacts of human activities well. The method could be used combining with the traditional methods in hydrological research.

scholarly journals Spatial and Temporal Changes in the Normalized Difference Vegetation Index and Their Driving Factors in the Desert/Grassland Biome Transition Zone of the Sahel Region of Africa

2020 ◽  
Vol 12 (24) ◽  
pp. 4119
Author(s):  
Shupu Wu ◽  
Xin Gao ◽  
Jiaqiang Lei ◽  
Na Zhou ◽  
Yongdong Wang
Keyword(s):  
Climate Change ◽  
Transition Zone ◽  
Human Activities ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Climate Factors ◽  
Desert Grassland ◽  
Temperature And Precipitation ◽  
Grassland Biome ◽  
Sahel Region

The ecological system of the desert/grassland biome transition zone is fragile and extremely sensitive to climate change and human activities. Analyzing the relationships between vegetation, climate factors (precipitation and temperature), and human activities in this zone can inform us about vegetation succession rules and driving mechanisms. Here, we used Landsat series images to study changes in the normalized difference vegetation index (NDVI) over this zone in the Sahel region of Africa. We selected 6315 sampling points for machine-learning training, across four types: desert, desert/grassland biome transition zone, grassland, and water bodies. We then extracted the range of the desert/grassland biome transition zone using the random forest method. We used Global Inventory Monitoring and Modelling Studies (GIMMS) data and the fifth-generation atmospheric reanalysis of the European Centre for Medium-Range Weather Forecasts (ERA5) meteorological assimilation data to explore the spatiotemporal characteristics of NDVI and climatic factors (temperature and precipitation). We used the multiple regression residual method to analyze the contributions of human activities and climate change to NDVI. The cellular automation (CA)-Markov model was used to predict the spatial position of the desert/grassland biome transition zone. From 1982 to 2015, the NDVI and temperature increased; no distinct trend was found for precipitation. The climate change and NDVI change trends both showed spatial stratified heterogeneity. Temperature and precipitation had a significant impact on NDVI in the desert/grassland biome transition zone; precipitation and NDVI were positively correlated, and temperature and NDVI were negatively correlated. Both human activities and climate factors influenced vegetation changes. The contribution rates of human activities and climate factors to the increase in vegetation were 97.7% and 48.1%, respectively. Human activities and climate factors together contributed 47.5% to this increase. The CA-Markov model predicted that the area of the desert/grassland biome transition zone in the Sahel region will expand northward and southward in the next 30 years.

scholarly journals Influences of Climate Change and Human Activities on NDVI Changes in China

2021 ◽  
Vol 13 (21) ◽  
pp. 4326
Author(s):  
Yu Liu ◽  
Jiyang Tian ◽  
Ronghua Liu ◽  
Liuqian Ding
Keyword(s):  
Climate Change ◽  
Human Activities ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Kendall Test ◽  
Dynamic Monitoring ◽  
Scientific Management ◽  
Liaohe River ◽  
Continental Basin ◽  
The Impact

The spatiotemporal evolution of vegetation and its influencing factors can be used to explore the relationships among vegetation, climate change, and human activities, which are of great importance for guiding scientific management of regional ecological environments. In recent years, remote sensing technology has been widely used in dynamic monitoring of vegetation. In this study, the normalized difference vegetation index (NDVI) and standardized precipitation‒evapotranspiration index (SPEI) from 1998 to 2017 were used to study the spatiotemporal variation of NDVI in China. The influences of climate change and human activities on NDVI variation were investigated based on the Mann–Kendall test, correlation analysis, and other methods. The results show that the growth rate of NDVI in China was 0.003 year−1. Regions with improved and degraded vegetation accounted for 71.02% and 22.97% of the national territorial area, respectively. The SPEI decreased in 60.08% of the area and exhibited an insignificant drought trend overall. Human activities affected the vegetation cover in the directions of both destruction and restoration. As the elevation and slope increased, the correlation between NDVI and SPEI gradually increased, whereas the impact of human activities on vegetation decreased. Further studies should focus on vegetation changes in the Continental Basin, Southwest Rivers, and Liaohe River Basin.

Quantitatively distinguish the impact of climate change and human activities on the vegetation changes in Mainland China based on the improved residual method

2020 ◽  
Author(s):  
Yahai Zhang ◽  
Aizhong Ye
Keyword(s):  
Climate Change ◽  
Human Activities ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Environmental Changes ◽  
Meteorological Data ◽  
Mainland China ◽  
Vegetation Changes ◽  
Ecological Protection ◽  
The Impact

<p>        Knowledge of the current severe global environmental changes, vegetation has faced the dual challenges posed by climate change and human activities. Quantitatively distinguishing the influence of climate change and human activities on vegetation changes is a key to develop adaptive ecological protection policies. This study used the Normalized Difference Vegetation Index (NDVI) and meteorological data from 1982 to 2015 to analyze the characteristic of vegetation changes and the relationship with climate factors in Mainland China. The contribution rates of climate change and human activities to vegetation dynamics are further calculated by the improved trend method of residual analysis. The results show that 68.81% vegetation of Mainland China is in a state of sustainable increase and cultivated vegetation (CV) and grass are the main greening vegetation types. The impact of human activities (54.45%-75.27%) on vegetation changes in Mainland China is higher than climate change (24.73%-45.46%). Human activities mainly affect grass, mixed coniferous broad-leaved forest (MCBF) and cultivated vegetation (CV), while swamp is more sensitive to climate change. The improved residual trend method considering temporal and spatial dimensions can reduce the uncertainty of the methods. This study provides a theoretical basis for future government implementation of ecological management.</p>

scholarly journals Urban Fire Severity and Vegetation Dynamics in Southern California

2020 ◽  
Vol 13 (1) ◽  
pp. 19
Author(s):  
Lauren E. H. Mathews ◽  
Alicia M. Kinoshita
Keyword(s):  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Current Knowledge ◽  
Fire Severity ◽  
Satellite Image ◽  
Burn Severity ◽  
Native Vegetation ◽  
Riparian Areas ◽  
The Impact

A combination of satellite image indices and in-field observations was used to investigate the impact of fuel conditions, fire behavior, and vegetation regrowth patterns, altered by invasive riparian vegetation. Satellite image metrics, differenced normalized burn severity (dNBR) and differenced normalized difference vegetation index (dNDVI), were approximated for non-native, riparian, or upland vegetation for traditional timeframes (0-, 1-, and 3-years) after eleven urban fires across a spectrum of invasive vegetation cover. Larger burn severity and loss of green canopy (NDVI) was detected for riparian areas compared to the uplands. The presence of invasive vegetation affected the distribution of burn severity and canopy loss detected within each fire. Fires with native vegetation cover had a higher severity and resulted in larger immediate loss of canopy than fires with substantial amounts of non-native vegetation. The lower burn severity observed 1–3 years after the fires with non-native vegetation suggests a rapid regrowth of non-native grasses, resulting in a smaller measured canopy loss relative to native vegetation immediately after fire. This observed fire pattern favors the life cycle and perpetuation of many opportunistic grasses within urban riparian areas. This research builds upon our current knowledge of wildfire recovery processes and highlights the unique challenges of remotely assessing vegetation biophysical status within urban Mediterranean riverine systems.

scholarly journals Coastal Mangrove Response to Marine Erosion: Evaluating the Impacts of Spatial Distribution and Vegetation Growth in Bangkok Bay from 1987 to 2017

2020 ◽  
Vol 12 (2) ◽  
pp. 220 ◽  
Author(s):  
Han Xiao ◽  
Fenzhen Su ◽  
Dongjie Fu ◽  
Qi Wang ◽  
Chong Huang
Keyword(s):  
Spatial Distribution ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Mangrove Ecosystem ◽  
Early Growth ◽  
Growth Stages ◽  
Human Disturbances ◽  
Vegetation Growth ◽  
Two Parameters ◽  
The Impact

Long time-series monitoring of mangroves to marine erosion in the Bay of Bangkok, using Landsat data from 1987 to 2017, shows responses including landward retreat and seaward extension. Quantitative assessment of these responses with respect to spatial distribution and vegetation growth shows differing relationships depending on mangrove growth stage. Using transects perpendicular to the shoreline, we calculated the cross-shore mangrove extent (width) to represent spatial distribution, and the normalized difference vegetation index (NDVI) was used to represent vegetation growth. Correlations were then compared between mangrove seaside changes and the two parameters—mangrove width and NDVI—at yearly and 10-year scales. Both spatial distribution and vegetation growth display positive impacts on mangrove ecosystem stability: At early growth stages, mangrove stability is positively related to spatial distribution, whereas at mature growth the impact of vegetation growth is greater. Thus, we conclude that at early growth stages, planting width and area are more critical for stability, whereas for mature mangroves, management activities should focus on sustaining vegetation health and density. This study provides new rapid insights into monitoring and managing mangroves, based on analyses of parameters from historical satellite-derived information, which succinctly capture the net effect of complex environmental and human disturbances.

scholarly journals A Simple Method for Converting 1-km Resolution Daily Clear-Sky LST into Real LST

2020 ◽  
Vol 12 (10) ◽  
pp. 1641
Author(s):  
Yunfei Zhang ◽  
Yunhao Chen ◽  
Jing Li ◽  
Xi Chen
Keyword(s):  
Land Surface ◽  
Missing Values ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Shortwave Radiation ◽  
Simple Method ◽  
The Real ◽  
Independent Variables ◽  
Clear Sky ◽  
Reconstruction Methods

Land-surface temperature (LST) plays a key role in the physical processes of surface energy and water balance from local through global scales. The widely used one kilometre resolution daily Moderate Resolution Imaging Spectroradiometer (MODIS) LST product has missing values due to the influence of clouds. Therefore, a large number of clear-sky LST reconstruction methods have been developed to obtain spatially continuous LST datasets. However, the clear-sky LST is a theoretical value that is often an overestimate of the real value. In fact, the real LST (also known as cloudy-sky LST) is more necessary and more widely used. The existing cloudy-sky LST algorithms are usually somewhat complicated, and the accuracy needs to be improved. It is necessary to convert the clear-sky LST obtained by the currently better-developed methods into cloudy-sky LST. We took the clear-sky LST, cloud-cover duration, downward shortwave radiation, albedo and normalized difference vegetation index (NDVI) as five independent variables and the real LST at the ground stations as the dependent variable to perform multiple linear regression. The mean absolute error (MAE) of the cloudy-sky LST retrieved by this method ranged from 3.5–3.9 K. We further analyzed different cases of the method, and the results suggested that this method has good flexibility. When we chose fewer independent variables, different clear-sky algorithms, or different regression tools, we also achieved good results. In addition, the method calculation process was relatively simple and can be applied to other research areas. This study preliminarily explored the influencing factors of the real LST and can provide a possible option for researchers who want to obtain cloudy-sky LST through clear-sky LST, that is, a convenient conversion method. This article lays the foundation for subsequent research in various fields that require real LST.

scholarly journals An LSWI-Based Method for Mapping Irrigated Areas in China Using Moderate-Resolution Satellite Data

2020 ◽  
Vol 12 (24) ◽  
pp. 4181
Author(s):  
Kunlun Xiang ◽  
Wenping Yuan ◽  
Liwen Wang ◽  
Yujiao Deng
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Statistical Data ◽  
Spatial Information ◽  
Hydrological Cycle ◽  
Mainland China ◽  
Mean Annual Precipitation ◽  
Irrigated Area ◽  
Moderate Resolution

Accurate spatial information about irrigation is crucial to a variety of applications, such as water resources management, water exchange between the land surface and atmosphere, climate change, hydrological cycle, food security, and agricultural planning. Our study proposes a new method for extracting cropland irrigation information using statistical data, mean annual precipitation and Moderate Resolution Imaging Spectroradiometer (MODIS) land cover type data and surface reflectance data. The approach is based on comparing the land surface water index (LSWI) of cropland pixels to that of adjacent forest pixels with similar normalized difference vegetation index (NDVI). In our study, we validated the approach over mainland China with 612 reference samples (231 irrigated and 381 non-irrigated) and found the accuracy of 62.09%. Validation with statistical data also showed that our method explained 86.67 and 58.87% of the spatial variation in irrigated area at the provincial and prefecture levels, respectively. We further compared our new map to existing datasets of FAO/UF, IWMI, Zhu and statistical data, and found a good agreement with the irrigated area distribution from Zhu’s dataset. Results show that our method is an effective method apply to mapping irrigated regions and monitoring their yearly changes. Because the method does not depend on training samples, it can be easily repeated to other regions.

scholarly journals Seasonal Variations of Daytime Land Surface Temperature and Their Underlying Drivers over Wuhan, China

2021 ◽  
Vol 13 (2) ◽  
pp. 323
Author(s):  
Liang Chen ◽  
Xuelei Wang ◽  
Xiaobin Cai ◽  
Chao Yang ◽  
Xiaorong Lu
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Maximum Temperature ◽  
Maximum Temperature Difference ◽  
Rapid Urbanization ◽  
The Impact ◽  
The City

Rapid urbanization greatly alters land surface vegetation cover and heat distribution, leading to the development of the urban heat island (UHI) effect and seriously affecting the healthy development of cities and the comfort of living. As an indicator of urban health and livability, monitoring the distribution of land surface temperature (LST) and discovering its main impacting factors are receiving increasing attention in the effort to develop cities more sustainably. In this study, we analyzed the spatial distribution patterns of LST of the city of Wuhan, China, from 2013 to 2019. We detected hot and cold poles in four seasons through clustering and outlier analysis (based on Anselin local Moran’s I) of LST. Furthermore, we introduced the geographical detector model to quantify the impact of six physical and socio-economic factors, including the digital elevation model (DEM), index-based built-up index (IBI), modified normalized difference water index (MNDWI), normalized difference vegetation index (NDVI), population, and Gross Domestic Product (GDP) on the LST distribution of Wuhan. Finally, to identify the influence of land cover on temperature, the LST of croplands, woodlands, grasslands, and built-up areas was analyzed. The results showed that low temperatures are mainly distributed over water and woodland areas, followed by grasslands; high temperatures are mainly concentrated over built-up areas. The maximum temperature difference between land covers occurs in spring and summer, while this difference can be ignored in winter. MNDWI, IBI, and NDVI are the key driving factors of the thermal values change in Wuhan, especially of their interaction. We found that the temperature of water area and urban green space (woodlands and grasslands) tends to be 5.4 °C and 2.6 °C lower than that of built-up areas. Our research results can contribute to the urban planning and urban greening of Wuhan and promote the healthy and sustainable development of the city.

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