Data integration of Sentinel-1 and Sentinel-2 for evaluating vegetation biomass and water status

被引：0

作者：

Pilia, S. ^{[1
]}

Fontanelli, G. ^{[1
]}

Santurri, L. ^{[1
]}

Ramat, G. ^{[1
]}

Baroni, F. ^{[1
]}

Santi, E. ^{[1
]}

Lapini, A. ^{[1
]}

Pettinato, S. ^{[1
]}

Paloscia, S. ^{[1
]}

机构：

[1] Nello Carrara Natl Res Council IFAC CNR, Inst Appl Phys, Florence, Italy

来源：

PROCEEDINGS OF 2023 IEEE INTERNATIONAL WORKSHOP ON METROLOGY FOR AGRICULTURE AND FORESTRY, METROAGRIFOR | 2023年

关键词：

Sentinel-1; Sentinel-2; data integration; Google Earth Engine; PRI; Water Cloud Model; IMAGES; NARROW; SOIL;

D O I：

10.1109/MetroAgriFor58484.2023.10424133

中图分类号：

S2 [农业工程];

学科分类号：

0828 ;

摘要：

The integration of microwave and multispectral data is an emerging technique allowing frequent monitoring of the vegetation biomass and health status. This study aims at integrating Sentinel-1 (S-1) and Sentinel-2 (S-2) acquisitions for estimating the biomass and assessing the water status of agricultural vegetation. The proposed method has been developed and tested on an agricultural area located in Tuscany, central Italy, by considering the S-1 and S-2 acquisitions collected during the summer season of 2022 on a grain sorghum plot. The method combines vegetation volumetric water content (m(v)) estimated from SAR data and optical/infrared vegetation indexes, in particular NDRE which presented the best correlation with the in-situ PRI measurements. The results show a relationship and trend between NDRE and m(v), although for a limited dataset.

引用

页码：694 / 698

页数：5

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