Arid
DOI10.3390/rs10091474
Using APAR to Predict Aboveground Plant Productivity in Semi-Arid Rangelands: Spatial and Temporal Relationships Differ
Gaffney, Rowan1; Porensky, Lauren M.1; Gao, Feng2; Irisarri, J. Gonzalo3; Durante, Martin4; Derner, Justin D.5; Augustine, David J.1
通讯作者Gaffney, Rowan
来源期刊REMOTE SENSING
ISSN2072-4292
出版年2018
卷号10期号:9
英文摘要

Monitoring of aboveground net primary production (ANPP) is critical for effective management of rangeland ecosystems but is problematic due to the vast extent of rangelands globally, and the high costs of ground-based measurements. Remote sensing of absorbed photosynthetically active radiation (APAR) can be used to predict ANPP, potentially offering an alternative means of quantifying ANPP at both high temporal and spatial resolution across broad spatial extents. The relationship between ANPP and APAR has often been quantified based on either spatial variation across a broad region or temporal variation at a location over time, but rarely both. Here we assess: (i) if the relationship between ANPP and APAR is consistent when evaluated across time and space; (ii) potential factors driving differences between temporal versus spatial models, and (iii) the magnitude of potential errors relating to space for time transformations in quantifying productivity. Using two complimentary ANPP datasets and remotely sensed data derived from MODIS and a Landsat/MODIS fusion data product, we find that slopes of spatial models are generally greater than slopes of temporal models. The abundance of plant species with different structural attributes, specifically the abundance of C4 shortgrasses with prostrate canopies versus taller, more productive C3 species with more vertically complex canopies, tended to vary more dramatically in space than over time. This difference in spatial versus temporal variation in these key plant functional groups appears to be the primary driver of differences in slopes among regression models. While the individual models revealed strong relationships between ANPP to APAR, the use of temporal models to predict variation in space (or vice versa) can increase error in remotely sensed predictions of ANPP.


英文关键词NDVI temporal spatial plant composition radiation use efficiency MODIS LANDSAT biomass ANPP
类型Article
语种英语
国家USA ; Argentina
收录类别SCI-E
WOS记录号WOS:000449993800154
WOS关键词RADIATION-USE EFFICIENCY ; CANOPY REFLECTANCE ; SHORTGRASS STEPPE ; UNITED-STATES ; VEGETATION ; NDVI ; PHOTOSYNTHESIS ; VARIABILITY ; MANAGEMENT ; ECOSYSTEM
WOS类目Remote Sensing
WOS研究方向Remote Sensing
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/212643
作者单位1.USDA ARS, Rangeland Resources & Syst Res Unit, Ft Collins, CO 80526 USA;
2.USDA ARS, Hydrol & Remote Sensing Lab, Beltsville, MD 20705 USA;
3.Univ Buenos Aires, LART IFEVA, Fac Agron, CONICET, Av San Martin 4453, RA-1417 Buenos Aires, DF, Argentina;
4.INTA EEA Concepcion Uruguay, RA-5461 Entre Rios, Argentina;
5.USDA ARS, Rangeland Resources & Syst Res Unit, Cheyenne, WY 82009 USA
推荐引用方式
GB/T 7714
Gaffney, Rowan,Porensky, Lauren M.,Gao, Feng,et al. Using APAR to Predict Aboveground Plant Productivity in Semi-Arid Rangelands: Spatial and Temporal Relationships Differ[J],2018,10(9).
APA Gaffney, Rowan.,Porensky, Lauren M..,Gao, Feng.,Irisarri, J. Gonzalo.,Durante, Martin.,...&Augustine, David J..(2018).Using APAR to Predict Aboveground Plant Productivity in Semi-Arid Rangelands: Spatial and Temporal Relationships Differ.REMOTE SENSING,10(9).
MLA Gaffney, Rowan,et al."Using APAR to Predict Aboveground Plant Productivity in Semi-Arid Rangelands: Spatial and Temporal Relationships Differ".REMOTE SENSING 10.9(2018).
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Gaffney, Rowan]的文章
[Porensky, Lauren M.]的文章
[Gao, Feng]的文章
百度学术
百度学术中相似的文章
[Gaffney, Rowan]的文章
[Porensky, Lauren M.]的文章
[Gao, Feng]的文章
必应学术
必应学术中相似的文章
[Gaffney, Rowan]的文章
[Porensky, Lauren M.]的文章
[Gao, Feng]的文章
相关权益政策
暂无数据
收藏/分享

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。