干旱区生态环境知识资源中心(Arid): Digital Mapping of Ecological Land Units using a Nationally Scalable Modeling Framework

Arid

DOI	10.2136/sssaj2018.09.0346
	Digital Mapping of Ecological Land Units using a Nationally Scalable Modeling Framework
	Maynard, Jonathan J.1; Nauman, Travis W.2; Salley, Shawn W.1; Bestelmeyer, Brandon T.1; Duniway, Michael C.2; Talbot, Curtis J.3; Brown, Joel R.3
通讯作者	Maynard, Jonathan J.
来源期刊	SOIL SCIENCE SOCIETY OF AMERICA JOURNAL
ISSN	0361-5995
EISSN	1435-0661
出版年	2019
卷号	83 期号:3 页码:666-686
英文摘要	Ecological site descriptions (ESDs) and associated state-and-transition models (STMs) provide a nationally consistent classification and information system for defining ecological land units for management applications in the United States. Current spatial representations of ESDs, however, occur via soil mapping and are therefore confined to the spatial resolution used to map soils within a survey area. Land management decisions occur across a range of spatial scales and therefore require ecological information that spans similar scales. Digital mapping provides an approach for optimizing the spatial scale of modeling products to best serve decision makers and have the greatest impact in addressing land management concerns. Here, we present a spatial modeling framework for mapping ecological sites using machine learning algorithms, soil survey field observations, soil survey geographic databases, ecological site data, and a suite of remote sensing-based spatial covariates (e.g., hyper-temporal remote sensing, terrain attributes, climate data, land-cover, lithology). Based on the theoretical association between ecological sites and landscape biophysical properties, we hypothesized that the spatial distribution of ecological sites could be predicted using readily available geospatial data. This modeling approach was tested at two study areas within the western United States, representing 6.1 million ha on the Colorado Plateau and 7.5 million ha within the Chihuahuan Desert. Results show our approach was effective in mapping grouped ecological site classes (ESGs), with 10-fold cross-validation accuracies of 70% in the Colorado Plateau based on 1405 point observations across eight expertly-defined ESG classes and 79% in the Chihuahuan Desert based on 2589 point observations across nine expertly-defined ESG classes. Model accuracies were also evaluated using external-validation datasets; resulting in 56 and 44% correct classification for the Colorado Plateau and Chihuahuan Desert, respectively. National coverage of the training and covariate data used in this study provides opportunities for a consistent national-scale mapping effort of ecological sites.
类型	Article
语种	英语
国家	USA
收录类别	SCI-E
WOS记录号	WOS:000473162500016
WOS关键词	SEMIAUTOMATED DISAGGREGATION ; QUANTITY DISAGREEMENT ; COLORADO PLATEAU ; SITE CONCEPTS ; SOIL ; CLASSIFICATION ; KNOWLEDGE ; MAPS
WOS类目	Soil Science
WOS研究方向	Agriculture
来源机构	United States Geological Survey
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/218883
作者单位	1.USDA ARS, Jornada Expt Range, Las Cruces, NM 88003 USA; 2.US Geol Survey, Southwest Biol Sci Ctr, Moab, UT 84532 USA; 3.USDA NRCS, Team Jornada Expt Range, Natl Ecol Site, Las Cruces, NM 88003 USA
推荐引用方式 GB/T 7714	Maynard, Jonathan J.,Nauman, Travis W.,Salley, Shawn W.,et al. Digital Mapping of Ecological Land Units using a Nationally Scalable Modeling Framework[J]. United States Geological Survey,2019,83(3):666-686.
APA	Maynard, Jonathan J..,Nauman, Travis W..,Salley, Shawn W..,Bestelmeyer, Brandon T..,Duniway, Michael C..,...&Brown, Joel R..(2019).Digital Mapping of Ecological Land Units using a Nationally Scalable Modeling Framework.SOIL SCIENCE SOCIETY OF AMERICA JOURNAL,83(3),666-686.
MLA	Maynard, Jonathan J.,et al."Digital Mapping of Ecological Land Units using a Nationally Scalable Modeling Framework".SOIL SCIENCE SOCIETY OF AMERICA JOURNAL 83.3(2019):666-686.