THE USE OF LANDSAT 8 AND SENTINEL-2 DATA AND METEROLOGICAL OBSERVATIONS FOR WINTER WHEAT YIELD ASSESSMENT

被引：0

作者：

Skakun, S. ^{[1
,2
]}

Franch, B. ^{[1
,2
]}

Vermote, E. ^{[2
]}

Roger, J. -C. ^{[1
,2
]}

Kussul, N. ^{[3
,4
]}

Masek, J. ^{[5
]}

机构：

[1] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA

[2] NASA, Goddard Space Flight Ctr, Code 619, Greenbelt, MD 20771 USA

[3] NAS Ukraine, Space Res Inst, UA-03680 Kiev, Ukraine

[4] SSA Ukraine, UA-03680 Kiev, Ukraine

[5] NASA, Goddard Space Flight Ctr, Code 618, Greenbelt, MD 20771 USA

来源：

2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019) | 2019年

基金：

美国国家航空航天局;

关键词：

Wheat; yield; Landsat; 8; Sentinel-2; Ukraine; REGIONAL-SCALE; CROP; SEASON; COVER; MODEL;

D O I：

10.1109/igarss.2019.8898245

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

This study focuses on winter wheat yield assessment from NASA's Harmonized Landsat Sentinel-2 (HLS) product and meteorological observations through phenological fitting. Vegetation indices (VIs), namely difference vegetation index (DVI), normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI2), extracted from satellite optical data, are fitted per pixel against accumulated growing degree days (AGDD) using a quadratic function. Accumulated VIs are correlated against winter wheat yields. Results show a better performance from DVI compared to NDVI and EVI2.

引用

页码：6291 / 6294

页数：4

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