alexa Estimation of Soil Moisture Percentage Using LANDSAT-based Moisture Stress Index | OMICS International | Abstract
ISSN: 2469-4134

Journal of Remote Sensing & GIS
Open Access

OMICS International organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations

700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)

Research Article

Estimation of Soil Moisture Percentage Using LANDSAT-based Moisture Stress Index

Pauline Welikhe1,2, Joseph Essamuah–Quansah1,2*, Souleymane Fall1,2 and Wendell McElhenney1

1Department of Agricultural and Environmental Sciences, Tuskegee University, Tuskegee, USA

2Geospatial and Climate Change Center, CAENS, Tuskegee University, Tuskegee, USA

*Corresponding Author:
Joseph Essamuah–Quansah
Department of Agricultural and Environmental Sciences
Tuskegee University, Tuskegee, USA
Tel: 3347278419
Fax: 3347278552
E-mail: [email protected]

Received Date: June 09, 2017; Accepted Date: June 22, 2017; Published Date: June 26, 2017

Citation: Welikhe P, Quansah JE, Fall S, Elhenney WMc (2017) Estimation of Soil Moisture Percentage Using LANDSAT-based Moisture Stress Index. J Remote Sensing & GIS 6: 200. doi: 10.4172/2469-4134.1000200

Copyright: © 2017 Welikhe P, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

The global agronomy community needs quick and frequent information on soil moisture variability and spatial trends in order to maximize crop production to meet growing food demands in a changing climate. However, in situ soil moisture measurement is expensive and labor intensive. Remote sensing based biophysical and predictive regression modeling approach have the potential for efficiently estimating soil moisture content over large areas. The study investigates the use of Moisture Stress Index (MSI) to estimate soil moisture variability in Alabama. In situ data were obtained from Soil Climate Analysis Network (SCAN) sites in Alabama and MSI developed from LANDSAT 8 OLI and LANDSAT 5 TM data. Pearson product moment correlation analysis showed that MSI strongly correlates with 16-day average growing season soil moisture measurements, with negative correlations of -0.519, -0.482 and -0.895 at 5, 10, and 20 cm soil depths respectively. The correlations of MSI and growing season moisture were low at sites where soil moisture was extremely low (<-0.3 at all depths). Simple linear regression model constructed for soil moisture at 20 cm depth (R²=0.79, p<0.05) correlated well with MSI values and was successfully used to estimate soil moisture percentage within a standard error of ± 3. Resulting MSI products were used to successfully produce the spatial distribution of soil moisture percentage at 20 cm depth. The study concludes that MSI is a good indicator of soil moisture conditions, and could be efficiently utilized in areas where in situ soil moisture data are unavailable.

Keywords

Peer Reviewed Journals
 
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2018-19
 
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

Agri & Aquaculture Journals

Dr. Krish

[email protected]

1-702-714-7001Extn: 9040

Biochemistry Journals

Datta A

[email protected]

1-702-714-7001Extn: 9037

Business & Management Journals

Ronald

[email protected]

1-702-714-7001Extn: 9042

Chemistry Journals

Gabriel Shaw

[email protected]

1-702-714-7001Extn: 9040

Clinical Journals

Datta A

[email protected]

1-702-714-7001Extn: 9037

Engineering Journals

James Franklin

[email protected]

1-702-714-7001Extn: 9042

Food & Nutrition Journals

Katie Wilson

[email protected]

1-702-714-7001Extn: 9042

General Science

Andrea Jason

[email protected]

1-702-714-7001Extn: 9043

Genetics & Molecular Biology Journals

Anna Melissa

[email protected]

1-702-714-7001Extn: 9006

Immunology & Microbiology Journals

David Gorantl

[email protected]

1-702-714-7001Extn: 9014

Materials Science Journals

Rachle Green

[email protected]

1-702-714-7001Extn: 9039

Nursing & Health Care Journals

Stephanie Skinner

[email protected]

1-702-714-7001Extn: 9039

Medical Journals

Nimmi Anna

[email protected]

1-702-714-7001Extn: 9038

Neuroscience & Psychology Journals

Nathan T

[email protected]

1-702-714-7001Extn: 9041

Pharmaceutical Sciences Journals

Ann Jose

[email protected]

1-702-714-7001Extn: 9007

Social & Political Science Journals

Steve Harry

[email protected]

1-702-714-7001Extn: 9042

 
© 2008- 2018 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version