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 : Varghese A. O. (검색결과 2 건)
- 무료
- 기관 내 무료
- 유료
-
Kritika Malik,K. R. L. Saranya,C. Sudhakar Reddy,A. O. Varghese 대한공간정보학회 2022 Spatial Information Research Vol.30 No.6
Species distribution models provide habitat mapping tools and produce scalable information to inform policy decisions. Integrating spatial statistical modelling with bioclimatic information identifies the contribution of the most critical variable in species occurrence and distribution. In the present study a suitable bioclimatic model, MaxEnt modelling algorithm is used for Dipterocarpus indicus, an endemic and endangered species by incorporating field inventory data.This model predicted a high probability of potential distribution area in the forests of Uttara Kannada, Chikmagalur, Shivamogga and Kannur. The highly suitable hábitats are distributed in protected áreas, namely Kudremukh, Mookambika, Pushpagiri, Sharavathi Valley, Shettihalli, Someshwara, Parambikulam, Peechi-Vazhani, Shendurney, Thattekadu Bird, Indira Gandhi (Anamalai), Kalakad, Mundanthurai and Kanyakumari. The Area Under Curve value for the potential distribution of species is observed at 0.894 for training data. The highest fractional predicted area was in the low elevation tropical wet evergreen forest region between 50 and 700 m. The contributions of the climatic variables in the model showed that precipitation in the coldest quarter was the most influential, followed by annual mean temperature and annual precipitation. This study aids in long-term conservation planning, monitoring, and managing potential habitats of endemic and endangered tree species.
-
Acreage estimation of kharif rice crop using Sentinel-1 temporal SAR data
Subbarao Nandepu V. V. S. S. Teja,Mani Jugal Kishore,Shrivastava Ashish,Srinivas Kumar Samayamantula,Varghese A. O. 대한공간정보학회 2021 Spatial Information Research Vol.29 No.4
Rice is one of the most important food crop in India covering about one-fourth of the total cropped area. India is the second largest producer and consumer of rice and accounts for 21% of the world’s total rice production. Rice is fundamentally a kharif season crop and grown in mainly rainfed areas. Recently there is a considerable increase in production, area and yield of rice crop in India. Temporal monitoring of crop area under cultivation is essential for the sustainable management of agricultural activities on both national and global levels. The present study is envisaged to estimate area under kharif rice using multi-temporal Sentinel-1 Synthetic Aperture Radar (SAR) data with dual polarization (VH and VV) in Bhandara district of Maharashtra. The geographical area of Bhandara district is 4087 square kilometres and lies in between 20640 030 ’ to 21600 180 ’ N latitude and 79440 930 ’ to 80080 700 ’ E longitude. The rice area is extracted using Random Forest (RF) classification techniques available in SNAP tool and validated using the ground observation collected from the field. An area of 1760 square kilometres was found under kharif rice out of 4087 square kilometres area of entire Bhandara district. The rice is predominant crop and covered around 43% of the total geographical area of Bhandara district during kharif season. The user accuracy (omission error), producer accuracy (commission error) for rice crop, overall accuracy and Kappa coefficients were 82.7, 90.0, 91% and 0.80, respectively. The study found that SAR data can be successfully used for acreage estimation with RF classifier.
연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
