scholarly journals Temporal and Spatial Changes and Driving Forces of NDVI From 1982 - 2015 in Qinba Mountains, China

2021 ◽  
Author(s):  
Yaru Zhang ◽  
Yi He ◽  
Yanlin Li ◽  
Liping Jia
Keyword(s):  
Human Activities ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Slow Growth ◽  
Driving Forces ◽  
Vegetation Coverage ◽  
Factors Affecting ◽  
Spatial Changes ◽  
Change Trend ◽  
Temporal And Spatial

Abstract The spatiotemporal variation and driving force of Normalized Difference Vegetation Index (NDVI) is helpful to regional ecological environment protection and natural resource management. Using the Sen and Mann–Kendall methods, Hurt index, Space transfer matrix and Geodetector, this study investigated the temporal and spatial changes and driving forces of NDVI during 1982 - 2015. The results showed that:（1）For the period 1982 to 2015, the high vegetation coverage was mainly distributed in Qinling Mountains and Daba mountain, while the value of NDVI was low in high altitude area in the west, low altitude in the East and Hanjiang River valley.（2）The change trend of NDVI in Qinba Mountains is mainly to maintain stable and slow growth. And the slow growth changes significantly. NDVI increased slowly mainly in the East and northwest.（3）The future change trend of NDVI in Qinba Mountain is mainly slow growth and stability, which indicates that the ecological construction in Qinba Mountains is good. (4) Through the geographical detector, the main factors affecting NDVI in Qinba Mountains are natural factors mainly including rainfall, soil type and digital elevation model (DEM), while human activities mainly including population density have little influence on NDVI in Qinba Mountains. Natural environment factors and human activities make a great difference on the spatial distribution of NDVI. This study provides a help for the sustainable development of the naturel environment in Qinba Mountains.

scholarly journals ANALYSIS ON TEMPORAL-SPATIAL CHANGES OF VEGETATION CVERRGE IN FARMING-PASTORAL ECOTONE OF INNER MONGOLIA

2018 ◽  
Vol XLII-3 ◽  
pp. 2053-2057
Author(s):  
X. Yan ◽  
J. Li ◽  
Z. Yang
Keyword(s):  
Inner Mongolia ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Dynamic Change ◽  
Animal Husbandry ◽  
Vegetation Coverage ◽  
Total Change ◽  
Vegetation Growth ◽  
Spatial Changes ◽  
Decomposition Models

Chen Barag Banner is located in the typical farming-pastoral ecotone of Inner Mongolia, and it is also the core area of Hulunbuir steppe. Typical agricultural and pastoral staggered production mode so that the vegetation growth of the region not only determines the local ecological environment, and animal husbandry production, but also have a significant impact on the whole Hulunbuir ecological security and economic development. Therefore, it is necessary to monitor the change of vegetation in this area. Based on 17 MODIS Normalized Difference Vegetation Index (NDVI) images, the authors reconstructed the dynamic change characteristics of Fraction vegetation coverage（FVC）in Chen Barag Banner from 2000 to 2016. In this paper, first at all, Pixel Decomposition Models was introduced to inversion FVC, and the time series of vegetation coverage was reconstructed. Then we analyzed the temporal-spatial changes of FVC by employing transition matrix. Finally, through image analyzing and processing, the results showed that the vegetation coverage in the study area was influenced by effectors including climate, topography and human actives. In the past 17 years, the overall effect of vegetation coverage showed a downward trend of fluctuation. The average vegetation coverage decreased from 58.81 % in 2000 to 48.14 % in 2016, and the area of vegetation cover degradation accounts for 40.09 % of the total change area. Therefore, the overall degradation trend was obvious.

scholarly journals Temporal and Spatial changes in Crop Patterns, Use of inputs and Hydrological Alteration in the case of Fogera floodplain, Ethiopia

2021 ◽  
Author(s):  
Mare Desta ◽  
Gete Zeleke ◽  
William. A. Payne ◽  
Wubneh Abebe
Keyword(s):  
Water Flow ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Temporal Trends ◽  
Primary Data ◽  
Nitrogen And Phosphorus ◽  
Rice Varieties ◽  
Hydrological Alteration ◽  
Spatial Changes ◽  
Temporal And Spatial

Abstract BauckgroundMore than half of the world's population consumes rice. The area under modern rice varieties has expanded, the use of chemical fertilizers and pesticides has increased in various countries. The hydrology of wetlands are also influenced by its chemical and physical characteristics. Hence, this research focused on temporal and spatial changes in crop patterns, input usage, and hydrological change in Fogera floodplain, with the objectives: a. what are the spatial and temporal trends in crops production pattern? b. What inputs have been used in the past and present to produce rice and other crops? c. What looks like the hydrological alteration of the area? The primary data was gathered through a questionnaire, focus group discussions, interviews, and field observations. Secondary data from Landsat imageries, SWAT input data, water flow, normalized difference vegetation index, and hydrological alteration of the site were collected. To analyze data, tables, graphs, and charts percentage, mean, and correlation were used. ResultNDVI results indicated that rice crop is growing while other variables are decreasing. artificial inputs are currently used but before the introduction of rice were not. Recession farming activities have also diminished wetland. Annual average water flow and rainfall have been trending upward. Flow of water with Nitrogen and Phosphorous has a negative correlation, with Pearson's values -0.069 and -0.072, respectively whereas the value 0.242 indicates that nitrogen and phosphorus have a positive relationship. ConclusionIn conclusion, these extended and intensification of farming practices have an impact on the biodiversity of fauna and flora of the area.

scholarly journals NDVI Variation and Its Responses to Climate Change on the Northern Loess Plateau of China from 1998 to 2012

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Tingting Ning ◽  
Wenzhao Liu ◽  
Wen Lin ◽  
Xiaoqiang Song
Keyword(s):  
Loess Plateau ◽  
Human Activities ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Climatic Factors ◽  
Time Lag ◽  
Annual Maximum ◽  
Vegetation Condition ◽  
Spatial Changes ◽  
Precipitation Changes

This study analyzed temporal and spatial changes of normalized difference vegetation index (NDVI) on the northern Loess Plateau and their correlation with climatic factors from 1998 to 2012. The possible impacts of human activities on the NDVI changes were also explored. The results showed that (1) the annual maximum NDVI showed an upward trend. The significantly increased NDVI and decreasing severe desertification areas demonstrate that the vegetation condition improved in this area. (2) Over the past decades, climate tended to be warmer and drier. However, the mean temperature significantly decreased and precipitation slightly increased from 1998 to 2012, especially in spring and summer, which was one of the major reasons for the increase in the annual maximum NDVI. Compared to temperature, vegetation was more sensitive to precipitation changes in this area. The NDVI and annual precipitation changes were highly synchronous over the first half of the year, while a 1-month time lag existed between the two variables during the second half of the year. (3) Positive human activities, including the “Grain for Green” program and successful environmental treatments at coal mining bases, were some of the other factors that improved the vegetation condition.

scholarly journals Determinizing the contributions of human activities and climate change on greening in the Beijing–Tianjin–Hebei Region, China

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Wei Cao ◽  
Dan Wu ◽  
Lin Huang ◽  
Mei Pan ◽  
Taoli Huhe
Keyword(s):  
Climate Change ◽  
Human Activities ◽  
Driving Forces ◽  
Vegetation Coverage ◽  
Agricultural Activities ◽  
Positive Effects ◽  
Nonlinear Responses ◽  
Spatial Differences ◽  
Temporal And Spatial ◽  
Region Scale

AbstractChina accounts for 25% of the global greening. There are temporal and spatial differences of China’s greening and intrinsic driving forces. Thus, it is crucial to determinize the contributions of human activities and climate change on greening at region scale. The Beijing–Tianjin–Hebei Region (BTHR) is one of the most active areas with human activities in China. It is necessary to explore negative or positive impacts of human activities on the regional greening or browning under climate change. A time series of annual vegetation coverage from satellite data was selected to quantify regional greening in the BTHR from 2000 to 2019 and their responses to climate change and human activities. Results showed generally widespread greening over the last 20 years at an average increased rate of 0.036 decade−1 in vegetation coverage (P < 0.01). Overall warmer and wetter climate across the BTHR were positively correlated with regional greening. The positive effects of human activities on greening accounted for 48.4% of the BTHR, especially the benefits of ecological restoration projects and the agricultural activities. Increases in vegetation coverage had resulted from the combined effects of climate change and human activities. Climate change had a stronger influence on vegetation coverage than human activities. Contributions of climate change to greening and browning was about 74.1% and < 20%, respectively. The decrease in vegetation coverage was mainly the results of the inhibition of human activities. More detailed socioeconomic and anthropogenic datasets are required for further analysis. Further research consideration would focus on the nonlinear responses of vegetation to climate change.

scholarly journals SPATIO-TEMPORAL CHANGE OF VEGETATION COVERAGE AND ITS DRIVING FORCES BASED ON LANDSAT IMAGES: A CASE STUDY OF CHANGCHUN CITY

2018 ◽  
Vol XLII-3 ◽  
pp. 295-298 ◽  
Author(s):  
L. Dong ◽  
H. Jiang ◽  
L. Yang
Keyword(s):  
Vegetation Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Driving Forces ◽  
Land Reclamation ◽  
Research Area ◽  
Vegetation Coverage ◽  
Landsat Images ◽  
Temperature And Precipitation ◽  
Spatio Temporal

Based on the Landsat images in 2006, 2011 and 2015, and the method of dimidiate pixel model, the Normalized Difference Vegetation Index (NDVI) and the vegetation coverage, this paper analyzes the spatio-temporal variation of vegetation coverage in Changchun, China from 2006 to 2015, and investigates the response of vegetation coverage change to natural and artificial factors. The research results show that in nearly 10 years, the vegetation coverage in Changchun dropped remarkably, and reached the minimum in 2011. Moreover, the decrease of maximum NDVI was significant, with a decrease of about 27.43&amp;thinsp;%, from 2006 to 2015. The vegetation coverage change in different regions of the research area was significantly different. Among them, the vegetation change in Changchun showed a little drop, and it decreased firstly and then increased slowly in Yushu, Nong’an and Dehui. In addition, the temperature and precipitation change, land reclamation all affect the vegetation coverage. In short, the study of vegetation coverage change contributes scientific and technical support to government and environmental protection department, so as to promote the coordinated development of ecology and economy.

Pemetaan Pulau Kecil Gelasa Kabupaten Bangka Tengah

2019 ◽  
Vol 2 (1) ◽  
pp. 11-14
Author(s):  
Wahyu Adi
Keyword(s):  
Coral Reefs ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Image Interpretation ◽  
Vegetation Coverage ◽  
Small Island ◽  
Shallow Waters ◽  
Small Islands ◽  
Seagrass Beds ◽  
Cover Density

Pulau Kecil Gelasa merupakan daerah yang belum banyak diteliti. Pemetaan ekosistem di pulau kecil dilakukan dengan bantuan citra Advanced Land Observing Satellite (ALOS). Penelitian terdahulu diketahui bahwa ALOS memiliki kemampuan memetakan terumbu karang dan padang lamun di perairan dangkal serta mampu memetakan kerapatan penutupan vegetasi. Metode interpretasi citra menggunakan alogaritma indeks vegetasi pada citra ALOS yaitu NDVI (Normalized Difference Vegetation Index), serta pendekatan Lyzengga untuk mengkoreksi kolom perairan. Hasil penelitian didapatkan luasan Padang Lamun di perairan dangkal 41,99 Ha, luasan Terumbu Karang 125,57 Ha. Hasil NDVI di daratan/ pulau kecil Gelasa untuk Vegetasi Rapat seluas 47,62 Ha; luasan penutupan Vegetasi Sedang 105,86 Ha; dan penutupan Vegetasi Jarang adalah 34,24 Ha.   Small Island Gelasa rarely studied. Mapping ecosystems on small islands with the image of Advanced Land Observing Satellite (ALOS). Previous research has found that ALOS has the ability to map coral reefs and seagrass beds in shallow water, and is able to map vegetation cover density. The method of image interpretation uses the vegetation index algorithm in the ALOS image, NDVI (Normalized Difference Vegetation Index), and the Lyzengga approach to correct the water column. The results of the study were obtained in the area of Seagrass Padang in the shallow waters of 41.99 ha, the area of coral reefs was 125.57 ha. NDVI results on land / small islands Gelasa for dense vegetation of 47.62 ha; area of Medium Vegetation coverage 105.86 Ha; and the coverage of Rare Vegetation is 34.24 Ha.

scholarly journals Spatial and Temporal Changes in Vegetation in the Ruoergai Region, China

Forests ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 76
Author(s):  
Yahui Guo ◽  
Jing Zeng ◽  
Wenxiang Wu ◽  
Shunqiang Hu ◽  
Guangxu Liu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Linear Trend ◽  
Spectral Characteristics ◽  
Growth Conditions ◽  
Temporal Changes ◽  
Vegetation Coverage ◽  
Dynamic Changes ◽  
Spatial And Temporal Changes ◽  
Temporal And Spatial

Timely monitoring of the changes in coverage and growth conditions of vegetation (forest, grass) is very important for preserving the regional and global ecological environment. Vegetation information is mainly reflected by its spectral characteristics, namely, differences and changes in green plant leaves and vegetation canopies in remote sensing domains. The normalized difference vegetation index (NDVI) is commonly used to describe the dynamic changes in vegetation, but the NDVI sequence is not long enough to support the exploration of dynamic changes due to many reasons, such as changes in remote sensing sensors. Thus, the NDVI from different sensors should be scientifically combined using logical methods. In this study, the Global Inventory Modeling and Mapping Studies (GIMMS) NDVI from the Advanced Very High Resolution Radiometer (AVHRR) and Moderate-resolution Imaging Spectroradiometer (MODIS) NDVI are combined using the Savitzky–Golay (SG) method and then utilized to investigate the temporal and spatial changes in the vegetation of the Ruoergai wetland area (RWA). The dynamic spatial and temporal changes and trends of the NDVI sequence in the RWA are analyzed to evaluate and monitor the growth conditions of vegetation in this region. In regard to annual changes, the average annual NDVI shows an overall increasing trend in this region during the past three decades, with a linear trend coefficient of 0.013/10a, indicating that the vegetation coverage has been continuously improving. In regard to seasonal changes, the linear trend coefficients of NDVI are 0.020, 0.021, 0.004, and 0.004/10a for spring, summer, autumn, and winter, respectively. The linear regression coefficient between the gross domestic product (GDP) and NDVI is also calculated, and the coefficients are 0.0024, 0.0015, and 0.0020, with coefficients of determination (R2) of 0.453, 0.463, and 0.444 for Aba, Ruoergai, and Hongyuan, respectively. Thus, the positive correlation coefficients between the GDP and the growth of NDVI may indicate that increased societal development promotes vegetation in some respects by resulting in the planting of more trees or the promotion of tree protection activities. Through the analysis of the temporal and spatial NDVI, it can be assessed that the vegetation coverage is relatively large and the growth condition of vegetation in this region is good overall.

scholarly journals Analysis of Drought Characteristics in Xilingol Grassland of Northern China Based on SPEI and Its Impact on Vegetation

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Siqin Tong ◽  
Yuhai Bao ◽  
Rigele Te ◽  
Qiyun Ma ◽  
Si Ha ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Pearson Correlation ◽  
Growing Season ◽  
Vegetation Coverage ◽  
Semiarid Region ◽  
Linear Regression Method ◽  
Upward Trend ◽  
Drought Effect ◽  
Positive Correlation

This research is based on the standardized precipitation evapotranspiration index (SPEI) and normalized difference vegetation index (NDVI) which represent the drought and vegetation condition on land. Take the linear regression method and Pearson correlation analysis to study the spatial and temporal evolution of SPEI and NDVI and the drought effect on vegetation. The results show that (1) during 1961–2015, SPEI values at different time scales showed a downward trend; SPEI-12 has a mutation in 1997 and the SPEI value significantly decreased after this year. (2) During 2000–2015, the annual growing season SPEI has an obvious upward trend in time and the apparent wetting spatially. (3) In the recent 16 years, the growing season NDVI showed an upward trend and more than 80% of the total area’s vegetation increased in Xilingol. (4) Vegetation coverage in Xilingol grew better in humid years and opposite in arid years. SPEI and NDVI had a significant positive correlation; 98% of the region showed positive correlation, indicating that meteorological drought affects vegetation growth more in arid and semiarid region. (5) The effect of drought on vegetation has lag effect, and the responses of different grassland types to different scales of drought were different.

scholarly journals Assessing the Effect of Drought on Winter Wheat Growth Using Unmanned Aerial System (UAS)-Based Phenotyping

2021 ◽  
Vol 13 (6) ◽  
pp. 1144
Author(s):  
Mahendra Bhandari ◽  
Shannon Baker ◽  
Jackie C. Rudd ◽  
Amir M. H. Ibrahim ◽  
Anjin Chang ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Grain Filling ◽  
Unmanned Aerial Systems ◽  
High Temporal Resolution ◽  
Wheat Growth ◽  
Spatial Domains ◽  
Temporal And Spatial

Drought significantly limits wheat productivity across the temporal and spatial domains. Unmanned Aerial Systems (UAS) has become an indispensable tool to collect refined spatial and high temporal resolution imagery data. A 2-year field study was conducted in 2018 and 2019 to determine the temporal effects of drought on canopy growth of winter wheat. Weekly UAS data were collected using red, green, and blue (RGB) and multispectral (MS) sensors over a yield trial consisting of 22 winter wheat cultivars in both irrigated and dryland environments. Raw-images were processed to compute canopy features such as canopy cover (CC) and canopy height (CH), and vegetation indices (VIs) such as Normalized Difference Vegetation Index (NDVI), Excess Green Index (ExG), and Normalized Difference Red-edge Index (NDRE). The drought was more severe in 2018 than in 2019 and the effects of growth differences across years and irrigation levels were visible in the UAS measurements. CC, CH, and VIs, measured during grain filling, were positively correlated with grain yield (r = 0.4–0.7, p < 0.05) in the dryland in both years. Yield was positively correlated with VIs in 2018 (r = 0.45–0.55, p < 0.05) in the irrigated environment, but the correlations were non-significant in 2019 (r = 0.1 to −0.4), except for CH. The study shows that high-throughput UAS data can be used to monitor the drought effects on wheat growth and productivity across the temporal and spatial domains.

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