http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Kashyap Rahul (검색결과 3 건)
- 무료
- 기관 내 무료
- 유료
-
Kashyap Rahul,Pandey Arvind Chandra,Parida Bikash Ranjan 대한공간정보학회 2021 Spatial Information Research Vol.29 No.6
Orography of Himalaya governs the regional weather system and monsoon of Indian sub-continent. The intense persistent precipitation in the form of rainfall during monsoon season causes landslides which are the most frequent naturally occurring hazards in the Himalaya. This study attempts to investigate the spatio-temporal variability of precipitation and their effect on precipitation triggered landslides during monsoon season (June–September) in relation to relief in Himalayan region by utilizing satellitederived precipitation products (GPM) over the span of 2000–2018 in addition to NASA Landslide Viewer, Global Landslide Catalog and Global Risk Data Platform data for landslides and ASTER DEM for elevation. The results exhibit that the Eastern Himalayas received the highest amount of precipitation of 2385 mm with intensity of 19.5 mm/day, followed by the Central Himalayas with 1860 mm and intensity of 17.5 mm/day and the least in the Western Himalayas with 1400 mm and intensity of 15 mm/day, respectively. The monsoon precipitation in the lower elevations (below 2600 m) are mostly responsible for causing a vast majority of the precipitation induced landslide events with a maximum of 68.66% in the Central Himalayas followed by the Western Himalayas at 62.23% and the least in the Eastern Himalayas at 41.16%. The overall accumulated precipitation and intensity during monsoon season and landslide distribution were strongly correlated with relief pattern. This comprehensive study signifies how relief regulated the occurrences of landslides in monsoon season and recommends vegetation cover and least interference of human-induced land use to alleviate the landslides.
-
Rahul Kashyap 대한공간정보학회 2022 Spatial Information Research Vol.30 No.5
Hydrocarbons are of significance for economic and environmental standpoints. Hydrocarbon microseepage alters the surface properties of land. Here, the detection of potential hydrocarbon microoseepage zone based on vegetation stress is carried out in the north-eastern Indian states of Assam and Meghalaya. A weighted overlay model, fed by 11 spectral wide and narrow band vegetation indices (VIs), is used to determine the effective VIs for detecting vegetation stress. Mineral alteration indices are also employed as proxies to detect potential hydrocarbon microseepage sites. Mineral alteration zones exhibiting vegetation stress are speculated to be potential hydrocarbon microseepage sites. VIs such as Red Edge Normalized Difference Vegetation Index (RENDVI), Normalized Difference Vegetation Index (NDVI), Lichtenthaler Index 1 (LIC1) and Simple Ratio Index (SRI) are more effective in detecting vegetation stress as they are sensitive to minor variations in chlorophyll content. The predominant vegetation stress is detected in south-east region of the study area in Jowai around Jaintia hills. The mineral alteration indices confirms that it is a potential hydrocarbon microseepage zone. Thus, remote sensing data can serve the dual purpose of fuel resource exploration and pollution source detection at once being cost effective, hazard free and convenient.
-
연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
