Dr. Damien Arvor Profile

Dr. Damien Arvor

at Univ Rennes 2

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 25 October 2016 Presentation + Paper

Monitoring of artificial water reservoirs in the Southern Brazilian Amazon with remote sensing data

Damien Arvor, Felipe Daher, Thomas Corpetti, Marianne Laslier, Vincent Dubreuil

Proceedings Volume 9998, 999816 (2016) https://doi.org/10.1117/12.2241905

KEYWORDS: Image resolution, Agriculture, Landsat, Remote sensing, Fusion energy, Clouds, Image fusion, Visualization, Spatial resolution, Earth observing sensors

Read Abstract +

The agricultural expansion in the Southern Brazilian Amazon has long been pointed out due to its severe impacts on tropical forests. But the last decade has been marked by a rapid agricultural transition which enabled to reduce pressure on forests through (i) the adoption of intensive agricultural practices and (ii) the diversification of activities. However, we suggest that this new agricultural model implies new pressures on environment and especially on water resources since many artificial water reservoirs have been built to ensure crop irrigation, generate energy, farm fishes, enable access to water for cattle or just for leisure. In this paper, we implemented a method to automatically map artificial water reservoirs based on time series of Landsat images. The method was tested in the county of Sorriso (State of Mato Grosso, Brazil) where we identified 521 water reservoirs by visual inspection on very high resolution images. 68 Landsat-8 images covering 4 scenes in 2015 were pre-classified and a final class (Terrestrial or Aquatic) was determined for each pixel based on a Dempster-Shafer fusion approach. Results confirmed the potential of the methodology to automatically and efficiently detect water reservoirs in the study area (overall accuracy = 0.952 and Kappa index = 0.904) although the methodology underestimates the total area in water bodies because of the spatial resolution of Landsat images. In the case of Sorriso, we mapped 19.4 km2 of the 20.8 km2 of water reservoirs initially delimited by visual interpretation, i.e. we underestimated the area by 5.9%.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years