Remotely piloted aircraft systems remote sensing can effectively retrieve ecosystem traits of alpine grasslands on the Tibetan Plateau at a landscape scale. Issue 3 (2nd February 2021)

• Record Type: Journal Article
• Authors: Tang, Ze; Zhang, Yangjian; Cong, Nan; Wang, Li; Zhu, Yixuan; Li, Zhaolei; Zhao, Guang
• Editors: Pettorelli, Nathalie; Murray, Nicholas
• Is Part Of: Remote sensing in ecology and conservation. Volume 7:Issue 3(2021)
• Page Start: 382
• Page End: 396
• Publication Date: 2021-02-02
• Subjects: Alpine grassland -- ecosystem trait -- landscape scale -- RPAS -- Tibetan Plateau -- visible spectrum; Remote sensing -- Periodicals; Ecology -- Research -- Periodicals; Ecology -- Methodology -- Periodicals; Ecology -- Remote sensing -- Periodicals; Nature conservation -- Methodology -- Periodicals; 577.0723
• DOI: 10.1002/rse2.196
• Languages: English
• ISSNs: 2056-3485

Abstract

Abstract: Ecosystem trait is a standardized description of biological features of a community, and it bridges individual plants and ecosystem. Conventionally most ecosystem trait data are collected from field survey and the generated data is hard to meet the requirements as set in the concept of ecosystem trait. To a great extent, remotely piloted aircraft systems (RPAS) remote sensing, which is capable of retrieving ecosystem traits across multiple scales, can overcome constraints in field plot survey. In this study, we selected alpine grassland ecosystem on the Tibetan Plateau (TP), which is under‐studied due to scarcity of field monitoring data, as the research target. A new data framework was proposed by integrating field plot and RPAS remote sensing data to map spatial patterns of ecosystem traits for the alpine grasslands. Across four landscapes on the TP, ecosystem traits of vegetation coverage (CVC), species number (CSN), individual number (CIN), above ground biomass (AGB), organic carbon content (OC%) and total nitrogen content (TN%) were retrieved. We also calculated Shannon's Diversity Index and Shannon's Evenness Index for each plot. The results showed that RPAS‐based high spatial resolution RGB image is capable of predicting both physical and chemical ecosystem traits for alpine grasslands on the TP. Remote sensing on physical traits are overall more efficient than on chemical traits, with the highest R 2 of 0.86 and 0.48 for physical trait and chemical one, respectively. The bands of Red and Green contributed more to the prediction model than band of Blue did, and the spectral mean value played a greater role than the spectral standard deviation. Based on the retrieved results, a set of spatial patterns on ecosystem traits can be revealed. This study represents an advance on ecosystem trait study and can significantly improve our understanding on ecosystem functions of the alpine ecosystem on the TP. Abstract : Remotely piloted aircraft systems visible remote sensing can effectively monitor ecosystem traits of alpine grassland at landscape scale. It also works efficiently in ecosystem traits retrieving and high‐resolution mapping, and helps us understand the response of these ecosystems to global changes at a scale beyond one site.