scholarly journals Tracking the Autumn Migration of the Bar-Headed Goose (Anser indicus) with Satellite Telemetry and Relationship to Environmental Conditions

2011 ◽  
Vol 2011 ◽  
pp. 1-10 ◽  
Author(s):  
Yaonan Zhang ◽  
Meiyu Hao ◽  
John Y. Takekawa ◽  
Fumin Lei ◽  
Baoping Yan ◽  
...  
Keyword(s):  
Environmental Conditions ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Habitat Type ◽  
Autumn Migration ◽  
Qinghai Lake ◽  
Vegetation Coverage ◽  
Migration Routes ◽  
Mountainous Regions ◽  
Stopover Sites

The autumn migration routes of bar-headed geese captured before the 2008 breeding season at Qinghai Lake, China, were documented using satellite tracking data. To assess how the migration strategies of bar-headed geese are influenced by environmental conditions, the relationship between migratory routes, temperatures, and vegetation coverage at stopovers sites estimated with the Normalized Difference Vegetation Index (NDVI) were analyzed. Our results showed that there were four typical migration routes in autumn with variation in timing among individuals in start and end times and in total migration and stopover duration. The observed variation may be related to habitat type and other environmental conditions along the routes. On average, these birds traveled about 1300 to 1500 km, refueled at three to six stopover sites and migrated for 73 to 83 days. The majority of the habitat types at stopover sites were lake, marsh, and shoal wetlands, with use of some mountainous regions, and farmland areas.

SVM Classification for Sensitive Land Parcels in Highway Route Selecting Based on ALOS Image Combining NDVI

2012 ◽  
Vol 518-523 ◽  
pp. 5623-5626
Author(s):  
Guo Qing Sun ◽  
Yu Huan Ren ◽  
Meng Meng Liu ◽  
Zhu Mei Liu ◽  
Ya Lan Liu
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Remote Sensing Data ◽  
Vegetation Coverage ◽  
Support Vector ◽  
High Effectiveness ◽  
Svm Classification ◽  
The Road ◽  
Mountainous Regions ◽  
City Group

In order to improve the efficiency and cost-saving investigation for sensitive land parcels for road route selecting, this paper demonstrates the methodology of Support Vector Machine (SVM) classification combining with the Normalized Difference Vegetation Index (NDVI) to identify the land parcels using ALOS remote sensing data. One part of the road corridor is taken as the study area in City Group of Changsha, Zhuzhou and Xiangtan, which is regarded as the two society pilot area. The results show that the high effectiveness and applicability of the method in high density vegetation coverage mountainous regions.

scholarly journals Assessing site-safeguard effectiveness and habitat preferences of Bar-headed Geese (Anser indicus) at their stopover sites within the Qinghai-Tibet Plateau using GPS/GSM telemetry

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Junjian Zhang ◽  
Yanbo Xie ◽  
Laixing Li ◽  
Nyambayar Batbayar ◽  
Xueqin Deng ◽  
...  
Keyword(s):  
Habitat Type ◽  
Nature Reserves ◽  
Tibet Plateau ◽  
Autumn Migration ◽  
High Plains ◽  
Migration Routes ◽  
Stopover Sites ◽  
Anser Indicus ◽  
Qinghai Tibet Plateau ◽  
National Nature Reserves

Abstract Background The Bar-headed Goose (Anser indicus) breeds across the high plains and plateau of Central Asia and winters in the Qinghai-Tibet Plateau (QTP), the Yunnan-Guizhou Plateau and the Indian sub-continent. Of the two recognized discrete flyways of the Bar-headed Goose, the Eastern Tibetan Flyway (ETF) is the larger, comprising at least six migration routes. However, we remain ignorant about their migratory connectivity, habitat use and effectiveness of site-safeguard mechanisms set in place for the species. Methods We tracked 30 ETF Bar-headed Geese from Chinese and Mongolian breeding areas to their wintering grounds using GPS/GSM transmitters, to determine their migration routes and stopover staging patterns within the QTP, overlaying these upon GIS layers of protected area status and habitat type, to model their habitat selection. Results In total, 14 tagged Bar-headed Geese provided information on their entire autumn migration and 4 geese on their entire spring migration. Qinghai Lake marked birds overwintered in the QTP (n = 2), geese tagged in Mongolia wintered either in the QTP (n = 3) or in India/Bangladesh (n = 9), representing three of the migration routes within the ETF. In total, tagged birds staged at 79 different stopover sites within QTP in autumn and 23 in spring, of which 65% (autumn) and 59% (spring) of all fixes fell within the boundaries of either National Nature Reserves (NNRs) or Important Birds Areas (IBAs) in the QTP. Bar-headed Geese predominantly occurred on four land-cover types: grassland (mostly by day), water bodies (at night), wetlands and bare substrates (salt flats, dry lake/river substrates and plough) with little change in proportion. Generalized linear mixed models comparing presence with pseudo-absence data suggested geese strongly selected for wetlands as staging habitat, avoiding bare substrates in spring. Conclusions Based on our limited observations of these tagged geese, this study is the first to show that the current designated National Nature Reserves in place in the staging areas within the QTP appear adequate to protect this increasing population. In addition, Hala Lake in Qinghai Province and adjacent areas used as initial QTP staging during autumn migration (currently outside of designated as NNRs/IBAs) are recommended for protection, based on their use by tagged birds from this study. Habitat modelling confirmed the importance of natural wetlands as feeding areas and safe areas of open water as roosting places.

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 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 Response of vegetation to submergence along Jingjiang Reach of the Yangtze River

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0251015
Author(s):  
Guoliang Zhu ◽  
Yitian Li ◽  
Zhaohua Sun ◽  
Shinjiro Kanae
Keyword(s):  
Yangtze River ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
High Elevation ◽  
Three Gorges Dam ◽  
Vegetation Coverage ◽  
Three Gorges ◽  
The Yangtze River ◽  
The Three Gorges ◽  
The Three Gorges Dam

This work explores the changes in vegetation coverage and submergence time of floodplains along the middle and lower reaches of the Yangtze River (i.e., the Jingjiang River) and the relations between them. As the Three Gorges Dam has been operating for more than 10 years, the original vegetative environment has been greatly altered in this region. The two main aspects of these changes were discovered by analyzing year-end image data from remote sensing satellites using a dimidiate pixel model, based on the normalized difference vegetation index, and by calculating water level and topographic data over a distance of 360 km from 2003–2015. Given that the channels had adjusted laterally, thus exhibiting deeper and broader geometries due to the Three Gorges Dam, 11 floodplains were classified into three groups with distinctive features. The evidence shows that, the floodplains with high elevation have formed steady vegetation areas and could hardly be affected by runoff and usually occupied by humans. The low elevation group has not met the minimal threshold of submerging time for vegetation growth, and no plants were observed so far. Based on the facts summed up from the floodplains with variable elevation, days needed to spot vegetation ranges from 70 to 120 days which happened typically near 2006 and between 2008 and 2010, respectively, and a negative correlation was detected between submergence time and vegetation coverage within a certain range. Thus, floods optimized by the Three Gorges Dam have directly influenced plant growth in the floodplains and may also affect our ability to manage certain types of large floods. Our conclusions may provide a basis for establishing flood criteria to manage the floodplain vegetation and evaluating possible increases in resistance caused by high-flow flooding when these floodplains are submerged.

scholarly journals Increased Stopover Duration and Low Body Condition of the Pied Flycatcher (Ficedula hypoleuca) at an Autumn Stopover Site

Animals ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 2208
Author(s):  
Bernice Goffin ◽  
Marcial Felgueiras ◽  
Anouschka R. Hof
Keyword(s):  
Environmental Change ◽  
Body Condition ◽  
Environmental Conditions ◽  
Ficedula Hypoleuca ◽  
Autumn Migration ◽  
Long Distance ◽  
Stopover Site ◽  
Stopover Duration ◽  
Stopover Sites ◽  
Over Time

Many long-distance migratory bird species are in decline, of which environmental changes, such as climate change and land-use changes, are thought to be important drivers. The effects of environmental change on the migration of these birds have often been studied during spring migration. Fewer studies have explored the impacts of environmental change on autumn migration, especially at stopover sites. However, stopover sites are important, as the quality of these sites is expected to change over time. We investigated impacts of local environmental conditions on the migration strategy and body condition of the Pied Flycatcher (Ficedula hypoleuca) at an autumn migration stopover site using long-term ringing data (1996–2018) and local environmental conditions. We found that although the arrival and departure dates of birds at the stopover site remained unchanged, the body condition (fat score) of the individuals caught decreased, and the stopover duration increased. This suggests that conditions at the stopover site during the autumn migration period have deteriorated over time. This study emphasizes the importance of suitable stopover sites for migratory birds and stresses that changes in environmental conditions during the autumn migration period may be contributing to the current decline in long-distance migratory passerines.

scholarly journals Impacts of Drought on Vegetation Assessed by Vegetation Indices and Meteorological Factors in Afghanistan

2020 ◽  
Vol 12 (15) ◽  
pp. 2433 ◽  
Author(s):  
Iman Rousta ◽  
Haraldur Olafsson ◽  
Md Moniruzzaman ◽  
Hao Zhang ◽  
Yuei-An Liou ◽  
...  
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Condition Index ◽  
Vegetation Coverage ◽  
P Value ◽  
Human Society ◽  
Time Series Regression ◽  
Drought Conditions

Drought has severe impacts on human society and ecosystems. In this study, we used data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) sensors to examine the drought effects on vegetation in Afghanistan from 2001 to 2018. The MODIS data included the 16-day 250-m composites of the Normalized Difference Vegetation Index (NDVI) and the Vegetation Condition Index (VCI) with Land Surface Temperature (LST) images with 1 km resolution. The TRMM data were monthly rainfalls with 0.1-degree resolution. The relationship between drought and index-defined vegetation variation was examined by using time series, regression analysis, and anomaly calculation. The results showed that the vegetation coverage for the whole country, reaching the lowest levels of 6.2% and 5.5% were observed in drought years 2001 and 2008, respectively. However, there is a huge inter-regional variation in vegetation coverage in the study period with a significant rising trend in Helmand Watershed with R = 0.66 (p value = 0.05). Based on VCI for the same two years (2001 and 2008), 84% and 72% of the country were subject to drought conditions, respectively. Coherently, TRMM data confirm that 2001 and 2008 were the least rainfall years of 108 and 251 mm, respectively. On the other hand, years 2009 and 2010 were registered with the largest vegetation coverage of 16.3% mainly due to lower annual LST than average LST of 14 degrees and partially due to their slightly higher annual rainfalls of 378 and 425 mm, respectively, than the historical average of 327 mm. Based on the derived VCI, 28% and 21% of the study area experienced drought conditions in 2009 and 2010, respectively. It is also found that correlations are relatively high between NDVI and VCI (r = 0.77, p = 0.0002), but slightly lower between NDVI and precipitation (r = 0.51, p = 0.03). In addition, LST played a key role in influencing the value of NDVI. However, both LST and precipitation must be considered together in order to properly capture the correlation between drought and NDVI.

scholarly journals Evolution of moult-migration is directly linked to aridity of the breeding grounds in North American passerines

2020 ◽  
Vol 16 (6) ◽  
pp. 20200155
Author(s):  
Claudie Pageau ◽  
Christopher M. Tonra ◽  
Mateen Shaikh ◽  
Nancy J. Flood ◽  
Matthew W. Reudink
Keyword(s):  
North American ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Autumn Migration ◽  
Western North America ◽  
Migration Distance ◽  
Migration Strategy ◽  
Breeding Grounds ◽  
Breeding Migration ◽  
Moult Migration

To avoid energy allocation conflicts, birds generally separate breeding, migration and moult during the annual cycle. North American passerines typically moult on the breeding grounds prior to autumn migration. However, some have evolved a moult-migration strategy in which they delay moult until stopping over during autumn migration. Rohwer et al . (2005) proposed the ‘push–pull hypothesis' as an explanation for the evolution of this moult strategy, but it has not been empirically tested. Poor conditions on the breeding grounds at the end of the summer would push birds to depart prior to moult, while productive stopover locations would pull them. We tested for a relationship between moult-migration and breeding grounds aridity as measured by the normalized difference vegetation index. Our results strongly support the ‘push' aspect of the push–pull hypothesis and indicate that arid breeding grounds, primarily in western North America, would drive species to evolve stopover moult-migration, although this relationship may depend upon migration distance.

Acquisitions of Vegetation Coverage and Cultivated Land Occupation Ratio of Taiyuan Valley Plain for Example Using CBERS-02B CCD Image

2012 ◽  
Vol 518-523 ◽  
pp. 5663-5667
Author(s):  
Shi Wei Li ◽  
Ji Long Zhang ◽  
Jian Sheng Yang
Keyword(s):  
Remote Sensing ◽  
Water Conservation ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Remote Sensing Image ◽  
Google Earth ◽  
Vegetation Coverage ◽  
Cultivated Land ◽  
Land Occupation ◽  
Coverage Ratio

Vegetation covering situation is very important for the quality of air quality, soil and water conservation ability and soil forming in an area. By using the remote sensing image of Taiyuan Valley Plain, the application of Normalized Difference Vegetation Index (NDVI) and unsupervised classification, the vegetation coverage map which includes non-cultivated land disposition and cultivated land disposition was obtained using ERDAS Imagine software. To evaluate the accuracy of the results, 200 points were sampled randomly, the high spatial resolution remote sensing image from Google Earth was used as the reference. The overall classification accuracy is 82%, with the Kappa statistic of 0.81. By counting the totally pixel acreage, it was gotten that the vegetation coverage was 46% and the cultivated land coverage ratio was 31% in the study area.

scholarly journals Mapping burned areas from landsat-8 imageries on mountainous region using reflectance changes

2018 ◽  
Vol 229 ◽  
pp. 04012
Author(s):  
Suwarsono ◽  
Hana Listi Fitriana ◽  
Indah Prasasti ◽  
Muhammad Rokhis Khomarudin
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Burned Area ◽  
Landsat 8 ◽  
Mountainous Region ◽  
Mountainous Regions ◽  
Burned Areas ◽  
Test And Evaluation ◽  
Normalized Burn Ratio ◽  
D Values

This research tried to detect a burned area that occurred in the mountainous region of Java Island. During this time, forest and land fires mostly occur in lowland areas in Sumatra and Kalimantan. However, it is possible that this phenomenon also occurs in mountainous regions, especially the mountainous regions of Java Island. The data used were Landsat-8, the latest generation of the Landsat series. The research location was on the Northeast slope of Mt. Ijen in East Java. The research methods include radiometric correction, data fusion, sample training retrieval, reflectance pattern analysis, Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR) extraction, separability analysis, parameter selection for burned area detection, parameter test, and evaluation. The results show that ρ5 and NBRL parameter shows the highest values of D-values (most sensitive), to detect the burned area. Then, compared to ρ5, NDVI and NBRS, Normalized Burn Ratio long (NBRL) provide better results in detecting burned areas.

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