Remote sensing of vegetation dynamics in agro-ecosystems using smap vegetation optical depth and optical vegetation indices

2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) Pub Date : 2017-07-26 DOI:10.1109/IGARSS.2017.8127964

M. Piles, Gustau Camps-Valls, D. Chaparro, D. Entekhabi, A. Konings, T. Jagdhuber

{"title":"Remote sensing of vegetation dynamics in agro-ecosystems using smap vegetation optical depth and optical vegetation indices","authors":"M. Piles, Gustau Camps-Valls, D. Chaparro, D. Entekhabi, A. Konings, T. Jagdhuber","doi":"10.1109/IGARSS.2017.8127964","DOIUrl":null,"url":null,"abstract":"The ESA's SMOS and the NASA's SMAP missions, launched in 2009 and 2015, respectively, are the first two missions having on-board L-band microwave sensors, which are very sensitive to the water content in soils and vegetation. Focusing on the vegetation signal at L-band, we have implemented an inversion approach for SMAP that allows deriving vegetation optical depth (VOD, a microwave parameter related to biomass and plant water content) alongside soil moisture, without reliance on ancillary optical information on vegetation. This work aims at using this new observational data to monitor the phenology of crops in major global agro-ecosystems and enhance present agricultural monitoring and prediction capabilities. Core agricultural regions have been selected worldwide covering major crops (corn, soybean, wheat, rice). The complementarity and synergies between the microwave vegetation signal, sensitive to biomass water-uptake dynamics, and optical indices, sensitive to canopy greenness, are explored. Results reveal the value of L-band VOD as an independent ecological indicator for global terrestrial biosphere studies. 1","PeriodicalId":6466,"journal":{"name":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"342 1","pages":"4346-4349"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IGARSS.2017.8127964","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 20

Abstract

The ESA's SMOS and the NASA's SMAP missions, launched in 2009 and 2015, respectively, are the first two missions having on-board L-band microwave sensors, which are very sensitive to the water content in soils and vegetation. Focusing on the vegetation signal at L-band, we have implemented an inversion approach for SMAP that allows deriving vegetation optical depth (VOD, a microwave parameter related to biomass and plant water content) alongside soil moisture, without reliance on ancillary optical information on vegetation. This work aims at using this new observational data to monitor the phenology of crops in major global agro-ecosystems and enhance present agricultural monitoring and prediction capabilities. Core agricultural regions have been selected worldwide covering major crops (corn, soybean, wheat, rice). The complementarity and synergies between the microwave vegetation signal, sensitive to biomass water-uptake dynamics, and optical indices, sensitive to canopy greenness, are explored. Results reveal the value of L-band VOD as an independent ecological indicator for global terrestrial biosphere studies. 1

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

基于smap植被光学深度和光学植被指数的农业生态系统植被动态遥感研究

ESA的SMOS和NASA的SMAP任务分别于2009年和2015年发射，是首批搭载l波段微波传感器的任务，它们对土壤和植被中的水分含量非常敏感。以l波段植被信号为重点，我们实现了一种SMAP反演方法，该方法可以在不依赖植被辅助光学信息的情况下，获得植被光学深度(VOD，与生物量和植物含水量相关的微波参数)和土壤水分。这项工作的目的是利用这些新的观测数据来监测全球主要农业生态系统中作物的物候，提高现有的农业监测和预测能力。在全球范围内选定了覆盖主要作物(玉米、大豆、小麦、水稻)的核心农业区域。探讨了对生物量水分吸收动态敏感的植被微波信号与对冠层绿度敏感的植被光学指数之间的互补和协同作用。结果表明，l波段VOD在全球陆地生物圈研究中具有独立的生态指标价值。1

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

自引率

0.00%

发文量