Acreage estimation of kharif rice crop using Sentinel-1 temporal SAR data

被引:0
作者
Nandepu V. V. S. S. Teja Subbarao
Jugal Kishore Mani
Ashish Shrivastava
K. Srinivas
A. O. Varghese
机构
[1] Jawaharlal Nehru Technological University,School of Spatial Information Technology
[2] National Remote Sensing Centre,Regional Remote Sensing Centre
[3] Indian Space Research Organisation,Central
来源
Spatial Information Research | 2021年 / 29卷
关键词
Rice; Sentinel-1 SAR data; RF classifier and Bhandara district;
D O I
暂无
中图分类号
学科分类号
摘要
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 20°64′03′' to 21°60′18′' N latitude and 79°44′93′' to 80°08′70′' 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.
引用
收藏
页码:495 / 505
页数:10
相关论文
共 102 条
  • [1] Bhatt CK(2018)Rice acreage estimation using Sentinel-1A dual polarised SAR data in Udham Singh Nagar (Uttarakhand) International Journal of Current Microbiology and Applied Sciences 108 100-106
  • [2] Nain AS(2016)Analysis of different polarimetric target decomposition methods in forest density classification using C band SAR data International Journal of Remote Sensing 21 1-6
  • [3] Varghese AO(2015)Polarimetric classification of C-band SAR data for forest density characterization Current Science undefined undefined-undefined
  • [4] Suryavanshi A(2018)Present and future Köppen-Geiger climate classification maps at 1-km resolution Scientific Data undefined undefined-undefined
  • [5] Joshi AK(2015)SAR image despeckling using refined lee filter IEEE Xplore undefined undefined-undefined
  • [6] Varghese AO(2001)Random forests Machine Learning undefined undefined-undefined
  • [7] Joshi AK(2011)MODIS NDVI time-series allow the monitoring of Eucalyptus plantation biomass Remote Sensing of Environment undefined undefined-undefined
  • [8] Beck HE(2012)High density biomass estimation for wetland vegetation using WorldView-2 imagery and random forest regression algorithm International Journal of Applied Earth Observation and Geoinformation undefined undefined-undefined
  • [9] Zimmermann NE(2014)Land-use/cover classification in a heterogeneous coastal landscape using RapidEye imagery: Evaluating the performance of random forest and support vector machines classifiers International Journal of Remote Sensing undefined undefined-undefined
  • [10] McVicar TR(2012)Modeling percent tree canopy cover: a pilot study Photogrammetric Engineering & Remote Sensing undefined undefined-undefined