Damage assessment of chilli thrips using high resolution multispectral satellite data

被引:0
作者
Prabhakar, Mathyam [1 ]
Thirupathi, Merugu [1 ]
Kumar, G. Srasvan [1 ]
Sravan, U. Sai [1 ]
Kalpana, M. [1 ]
Gopinath, K. A. [1 ]
Kumar, N. Ravi [1 ]
机构
[1] ICAR Cent Res Inst Dryland Agr, Hyderabad 500059, Telangana, India
来源
JOURNAL OF AGROMETEOROLOGY | 2019年 / 21卷 / 04期
关键词
Pest; crop stress; spectral vegetation index; remote sensing; spatial distribution; VEGETATION; COTTON; WATER; BLIGHT; INDEX; WHEAT;
D O I
暂无
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Remote sensing technology offers an effective, rapid and reliable tool for assessing pest severity in vegetation. Ground based hyperspectral radiometry studies revealed significant difference in the reflectance spectra between healthy and thrip damaged vegetation. Space borne multispectral reflectance from Sentinel 2A satellite data of chilli thrip infested canopy has significant differences in red region (Band 4 - 664.6 nm), NIR region (Bands 5, 6, 7, 8 & 8A having central wavelengths at 704.1, 740.5, 782.8 & 832.8 nm, respectively) and SWIR region (Bands 11 & 12 having central wavelengths at 1613.7 and 2202.4 nm). In this study, an attempt was made to discriminate healthy and pest affected chilli crop in the multispectral satellite imagery using several multispectral vegetation indices. Of these, land surface water index, LSWI (p=0.018) and normalized difference water index, NDWI (p=0.001) were found significant. These indices were used to classify chilli fields in the satellite imagery into severe, moderate and healthy classes. Superior performance of LSWI over NDWI with overall accuracy of 93.80 and Kappa Coefficient of 0.89 was observed. Moran's Index was used to study the spatial distribution of chilli thrips and observed strong clustering (I= 0.9073, p=0.0001).
引用
收藏
页码:480 / 487
页数:8
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