Dr. Sara Parrilli Profile

Dr. Sara Parrilli

at Ctr Italiano Ricerche Aerospaziali

SPIE Involvement:

Author

Publications (2)

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 | 19 October 2023 Presentation + Paper

Progressive monitoring of micro-dumps: a case study over the Campania Region (Italy)

Luca Cicala, Francesco Gargiulo, Sara Parrilli, Donato Amitrano, Gianpaolo Pigliasco

Proceedings Volume 12734, 1273405 (2023) https://doi.org/10.1117/12.2679725

KEYWORDS: Remote sensing, Decision support systems, Data fusion, Satellite imaging, Environmental monitoring, Earth observing sensors

Read Abstract +

Illegal micro-dumps are a plague affecting many industrialized and developing countries. Their monitoring requires continuous data to be provided to decision makers for implementation of mitigation actions. In this context, an optimized monitoring strategy is key since the resources assigned to the activities necessary for the specific characterization of the sites and for remediation purposes are typically limited by budget constraints. This work proposes a progressive monitoring framework based on remote sensing data aimed at the optimization of the available on-ground monitoring resources. A set of different remote sensing technologies and processing tools is proposed in order to acquire and exploit increasingly spatially detailed information with the objective to select areas needing on-ground inspections. The case study here presented exploits, as first step, satellite remote sensing to detect areas potentially affected by micro-dumps. Then, airborne acquisitions are exploited to confirm what observed from space. Finally, close-range drone remote sensing is exploited to characterize the selected sites in terms of waste volume estimation. Moreover, a decision support system is designed in order to digitalize the proposed monitoring process. The paper is focused on the employment of remote sensing products and models in the decision support workflow. The process is tailored on the specific use case of illegal waste monitoring and validated through a case study in Southern Italy.

Proceedings Article | 9 October 2018 Paper

A case study on the detection of illegal dumps with GIS and remote sensing images

C. Angelino, M. Focareta, S. Parrilli, L. Cicala, G. Piacquadio, G. Meoli, M. De Mizio

Proceedings Volume 10790, 107900M (2018) https://doi.org/10.1117/12.2325557

KEYWORDS: Satellites, Geographic information systems, Remote sensing, Satellite imaging, Image processing, Earth observing sensors

Read Abstract +

This paper presents a case study about the detection of illegal dumps from optical satellite images in a large territory falling in the provinces of Naples and Caserta, Southern Italy. This location is also known with the term "Terra dei Fouchi" because in this area is particularly widespread the phenomenon of waste burning and, over the past decades, there have been many landfills of hazardous waste of industrial origin. In order to contrast this phenomenon, the government of the Campania Region organized some prevention, monitoring and repression activities. In particular, the monitoring activities are employed by periodic inspection of sites, which are often object of illegal deposits (former quarries, illegal dumps, as well as city and country roads). The periodic inspection is usually performed by patrols of the company SMA Campania (the in-house regional company, specialized in environmental protection), and law enforcement agencies. Since early warning of illegal and the quick characterization of the detected sites is a key factor for effective resource allocation in the fight against illegal waste dumping, as part of a project, the periodic monitoring inspections of the local environmental agency have been supported with multi-temporal satellite images. The detection has been performed via expert photo-interpretation in order to achieve a high level of accuracy and reliable maps. However, in order to reduce this time consuming task, a multi-features detection algorithm has been implemented. Detected sites have been then classified according to 4 major characteristics (type, state, location and activity) of the dumps. Moreover, a multi-temporal analysis has been performed and it allowed following the evolution of the phenomenon. This approach was effective in both finding new illegal spills (with associated macro classification) and to follow the evolution (in terms of extension and persistence) of landfills already found in the past.

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