Back to Search Start Over

Observation and Monitoring of Mangrove Forests Using Remote Sensing: Opportunities and Challenges.

Authors :
Giri, Chandra
Source :
Remote Sensing. Sep2016, Vol. 8 Issue 9, p783. 8p.
Publication Year :
2016

Abstract

Mangrove forests, distributed in the tropical and subtropical regions of the world, are in a constant flux. They provide important ecosystem goods and services to nature and society. In recent years, the carbon sequestration potential and protective role of mangrove forests from natural disasters is being highlighted as an effective option for climate change adaptation and mitigation. The forests are under threat from both natural and anthropogenic forces. However, accurate, reliable, and timely information of the distribution and dynamics of mangrove forests of the world is not readily available. Recent developments in the availability and accessibility of remotely sensed data, advancement in image pre-processing and classification algorithms, significant improvement in computing, availability of expertise in handling remotely sensed data, and an increasing awareness of the applicability of remote sensing products has greatly improved our scientific understanding of changing mangrove forest cover attributes. As reported in this special issue, the use of both optical and radar satellite data at various spatial resolutions (i.e., 1 m to 30 m) to derive meaningful forest cover attributes (e.g., species discrimination, above ground biomass) is on the rise. This multi-sensor trend is likely to continue into the future providing a more complete inventory of global mangrove forest distributions and attribute inventories at enhanced temporal frequency. The papers presented in this "Special Issue" provide important remote sensing monitoring advancements needed to meet future scientific objectives for global mangrove forest monitoring from local to global scales. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
8
Issue :
9
Database :
Academic Search Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
118431131
Full Text :
https://doi.org/10.3390/rs8090783