Evidence map›Paper›PMID 21135917›Full record

ArticleSpatial and spatio-temporal epidemiology2010

Generating land cover boundaries from remotely sensed data using object-based image analysis: overview and epidemiological application.

Susan K Maxwell

Abstract read
In one paragraph

Article in Spatial and spatio-temporal epidemiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Susan K MaxwellBioMedware Inc., 3526 W. Liberty Rd., Suite 100, Ann Arbor, MI 48103, United States. Maxwell@biomedware.com

Funding

NCI NIH HHS HHSN261200900024C
6 · The paper itself

Abstract

Satellite imagery and aerial photography represent a vast resource to significantly enhance environmental mapping and modeling applications for use in understanding spatio-temporal relationships between environment and health. Deriving boundaries of land cover objects, such as trees, buildings, and crop fields, from image data has traditionally been performed manually using a very time consuming process of hand digitizing. Boundary detection algorithms are increasingly being applied using object-based image analysis (OBIA) technology to automate the process. The purpose of this paper is to present an overview and demonstrate the application of OBIA for delineating land cover features at multiple scales using a high resolution aerial photograph (1 m) and a medium resolution Landsat image (30 m) time series in the context of a pesticide spray drift exposure application.

Indexed as

AgricultureImage Interpretation, Computer-AssistedPhotographySoftwareEcosystemEnvironmental HealthEnvironmental MonitoringEnvironmental PollutantsGeographic Information SystemsHumansPesticidesRemote Sensing TechnologySensitivity and SpecificityEnvironmental PollutantsPesticidesaerial photographimage segmentationLandsatpesticide exposure

Identifiers

PMID21135917
PMCPMC2996831

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.