Spatial database modeling for mangrove forests mapping; example of two estuarine systems in Brazil

This work considers mangrove cover changes in two subtropical estuaries in the southeastern coast of Brazil: Cananéia-Iguape Coastal System and Santos Estuarine System. A sequence of Landsat images from 1985 to 2014 from both areas was segmented, classified and analyzed in order to develop a systema...

Full description

Saved in:
Bibliographic Details
Published in:Modeling earth systems and environment 2016-06, Vol.2 (2), p.1-12, Article 73
Main Authors: Conti, Luis Américo, de Araújo, Carlos Alberto Sampaio, Cunha-Lignon, Marília
Format: Article
Language:English
Subjects:
Brackishwater environment
Change detection
Chemistry and Earth Sciences
Coastal environments
Coastal resources
Computer Science
Data processing
Detection
Earth and Environmental Science
Earth Sciences
Earth System Sciences
Ecosystems
Environment
Environmental monitoring
Estuaries
Estuarine environments
Frameworks
Geographical information systems
Handling
Landsat
Landsat satellites
Mangrove swamps
Mangroves
Math. Appl. in Environmental Science
Mathematical Applications in the Physical Sciences
Modelling
Original Article
Physics
Remote sensing
Resource conservation
Satellite imagery
Spatial data
Statistics for Engineering
Variation
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This work considers mangrove cover changes in two subtropical estuaries in the southeastern coast of Brazil: Cananéia-Iguape Coastal System and Santos Estuarine System. A sequence of Landsat images from 1985 to 2014 from both areas was segmented, classified and analyzed in order to develop a systematic GIS approach for identifying and characterizing mangrove fragments in such estuaries and how they change over time. The main goal of our work is to propose a unified hierarchical spatial database model in a GIS framework developed to incorporate different types of spatial information such as spectral (e.g. vegetation indices), spatial (e.g. fragmentation indices) and temporal (e.g. change detection) at different scales. The examples analyzed showed that changes and fluctuations in mangrove habitats could be identified and characterized revealing potential tools for handling and analyzing data focused on environmental monitoring and the coastal resource protection and conservation.
ISSN:2363-6203
2363-6211
DOI:10.1007/s40808-016-0129-3