2018
DOI: 10.3390/ijgi7100397
|View full text |Cite
|
Sign up to set email alerts
|

CO-RIP: A Riparian Vegetation and Corridor Extent Dataset for Colorado River Basin Streams and Rivers

Abstract: Here we present “CO-RIP”, a novel spatial dataset delineating riparian corridors and riparian vegetation along large streams and rivers in the United States (U.S.) portion of the Colorado River Basin. The consistent delineation of riparian areas across large areas using remote sensing has been a historically complicated process partially due to differing definitions in the scientific and management communities regarding what a “riparian corridor” or “riparian vegetation” represents. We use valley-bottoms to de… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
9
0

Year Published

2019
2019
2023
2023

Publication Types

Select...
7
1

Relationship

1
7

Authors

Journals

citations
Cited by 16 publications
(10 citation statements)
references
References 40 publications
(57 reference statements)
0
9
0
Order By: Relevance
“…It is available at the spatial resolution of 0.6 to 2 meters with very low cloud coverage and consists of repeat images during the growing season with two or three year cycles for more than 15 years [1]. It has been a unique choice for a variety of geospatial mapping applications, such as analysis of land cover and land use change [2][3][4], evaluation of ecosystem services [5][6][7], monitoring of forest health [8][9][10][11], and assessment of urban green infrastructure [12,13]. The NAIP imagery will likely continue to be the one of the best data sources for many research and operational efforts that need high-resolution multispectral imagery for feature extraction, change detection, or collection of ground truth for validate coarse-resolution satellite products.…”
Section: Introductionmentioning
confidence: 99%
“…It is available at the spatial resolution of 0.6 to 2 meters with very low cloud coverage and consists of repeat images during the growing season with two or three year cycles for more than 15 years [1]. It has been a unique choice for a variety of geospatial mapping applications, such as analysis of land cover and land use change [2][3][4], evaluation of ecosystem services [5][6][7], monitoring of forest health [8][9][10][11], and assessment of urban green infrastructure [12,13]. The NAIP imagery will likely continue to be the one of the best data sources for many research and operational efforts that need high-resolution multispectral imagery for feature extraction, change detection, or collection of ground truth for validate coarse-resolution satellite products.…”
Section: Introductionmentioning
confidence: 99%
“…Specifically, the validation dataset was generated utilizing a simple random approach distributed over the corresponding Planet Scope imagery associated with individual flood dates. The validation samples were classified using a digital ocular sampling approach [68,69]. An individual sampler performed a visual interpretation on the Planet Scope imagery, constraining the interpretation to a 3 × 3 pixel neighborhood equating to the approximate resolution of the surface water products generated (10 m GSD).…”
Section: Evaluation Designmentioning
confidence: 99%
“…Also regarding the quality of input data, the riparian zone can be estimated in a more sophisticated way. The application of a standard riparian distance to all waterbodies could be improved by instead using variable riparian buffer distances based on the size of waterbodies and bank geomorphology, as suggested by other studies [15,24].…”
Section: Potential For Additional Data and Tool Improvementsmentioning
confidence: 99%
“…The most commonly used wetland remote sensing data are Landsat multispectral imagery, which as of Landsat 8 is 30 m in resolution for most bands, repeats its cycle every 16 days, includes 11 bands, and is freely available [13]. Researchers have achieved accurate wetland identification results by incorporating Landsat imagery, specifically from the Landsat 8 Operational Land Imagery (OLI) satellite (e.g., [14][15][16][17][18]). At this spatial resolution, however, it is unlikely that approaches could identify exact wetland locations obtained through field delineations by experts, but it is possible that such data could rule out large areas as not being likely to include wetlands.…”
Section: Introductionmentioning
confidence: 99%