Remote sensing techniques: mapping and monitoring of mangrove ecosystem—a review

Abstract Mangrove forests are considered to be the most productive ecosystem yet vanishing rapidly over world. They mostly found in intertidal zone and sheltered by seacoast. Mangroves have potential socio-economic benefits such as protecting shoreline from storm soil erosion, flood flow control, acting a carbon sink, provides fertile breeding ground for marine species fauna. It also acts source of income providing various forest products. Restoration conservation mangrove remain big challenge due large inaccessible areas covered mangroves which makes field assessment difficult time-consuming. Remote sensing along with digital image classification approaches seem promising better accurate results mapping monitoring ecosystem. This review paper aims provide comprehensive summary work undertaken, addresses remote techniques applied ecosystem, summarize their limitation. For that analyzed compared based on type used its spectral resolution, spatial other related features accuracy derive specific class information mangroves. The studies can classified into pixel-based, object-based, knowledge-based classifiers. satellite data ranged light detection ranging (LiDAR), hyperspectral multispectral optical imagery, synthetic aperture radar (SAR), aerial imagery. Supervised state art machine learning/deep learning algorithms use both pixel-based object-based combined approach widely purpose, recent development evolution these techniques. There is huge future scope study performance combination high resolution imageries, SAR LiDAR, multi-sensor, multiresolution, temporal data.