Remotely piloted aircraft systems remote sensing can effectively retrieve ecosystem traits of alpine grasslands on the Tibetan Plateau at a landscape scale
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 ecos...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-09-01
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| Series: | Remote Sensing in Ecology and Conservation |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/rse2.196 |
| _version_ | 1818908683977883648 |
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| author | Ze Tang Yangjian Zhang Nan Cong Li Wang Yixuan Zhu Zhaolei Li Guang Zhao |
| author_facet | Ze Tang Yangjian Zhang Nan Cong Li Wang Yixuan Zhu Zhaolei Li Guang Zhao |
| author_sort | Ze Tang |
| collection | DOAJ |
| description | 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 R2 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. |
| first_indexed | 2024-12-19T22:14:55Z |
| format | Article |
| id | doaj.art-732a03d4b29242169692088660507fbe |
| institution | Directory Open Access Journal |
| issn | 2056-3485 |
| language | English |
| last_indexed | 2024-12-19T22:14:55Z |
| publishDate | 2021-09-01 |
| publisher | Wiley |
| record_format | Article |
| series | Remote Sensing in Ecology and Conservation |
| spelling | doaj.art-732a03d4b29242169692088660507fbe2022-12-21T20:03:48ZengWileyRemote Sensing in Ecology and Conservation2056-34852021-09-017338239610.1002/rse2.196Remotely piloted aircraft systems remote sensing can effectively retrieve ecosystem traits of alpine grasslands on the Tibetan Plateau at a landscape scaleZe Tang0Yangjian Zhang1Nan Cong2Li Wang3Yixuan Zhu4Zhaolei Li5Guang Zhao6Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 ChinaKey Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 ChinaKey Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 ChinaPeking University Shenzhen Graduate School Shenzhen 518055 ChinaKey Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 ChinaCollege of Resources and Environment Shandong Agricultural University Taian 271018 ChinaKey Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 ChinaAbstract 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 R2 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.https://doi.org/10.1002/rse2.196Alpine grasslandecosystem traitlandscape scaleRPASTibetan Plateauvisible spectrum |
| spellingShingle | Ze Tang Yangjian Zhang Nan Cong Li Wang Yixuan Zhu Zhaolei Li Guang Zhao Remotely piloted aircraft systems remote sensing can effectively retrieve ecosystem traits of alpine grasslands on the Tibetan Plateau at a landscape scale Remote Sensing in Ecology and Conservation Alpine grassland ecosystem trait landscape scale RPAS Tibetan Plateau visible spectrum |
| title | Remotely piloted aircraft systems remote sensing can effectively retrieve ecosystem traits of alpine grasslands on the Tibetan Plateau at a landscape scale |
| title_full | Remotely piloted aircraft systems remote sensing can effectively retrieve ecosystem traits of alpine grasslands on the Tibetan Plateau at a landscape scale |
| title_fullStr | Remotely piloted aircraft systems remote sensing can effectively retrieve ecosystem traits of alpine grasslands on the Tibetan Plateau at a landscape scale |
| title_full_unstemmed | Remotely piloted aircraft systems remote sensing can effectively retrieve ecosystem traits of alpine grasslands on the Tibetan Plateau at a landscape scale |
| title_short | Remotely piloted aircraft systems remote sensing can effectively retrieve ecosystem traits of alpine grasslands on the Tibetan Plateau at a landscape scale |
| title_sort | remotely piloted aircraft systems remote sensing can effectively retrieve ecosystem traits of alpine grasslands on the tibetan plateau at a landscape scale |
| topic | Alpine grassland ecosystem trait landscape scale RPAS Tibetan Plateau visible spectrum |
| url | https://doi.org/10.1002/rse2.196 |
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