Mapping Land-Cover and Mangrove Structures with Remote Sensing Techniques: A Contribution to a Synoptic GIS in Support of Coastal Management in North Brazil

Abstract

This article deals with the development and application of a cartographic database for a synoptic Geographic Information System (GIS). Its purpose is the storage and evaluation of the heterogeneous datasets of the interdisciplinary scientific research program MADAM (Mangrove Dynamics and Management), which aims to develop recommendations for a tailored integrated coastal management scheme for the mangrove ecosystem at Braganca (North Brazil). The article describes the integration of remote sensing data, aerial photographs, as well as point data provided by fieldwork from different scientific fields. Using various innovative processing techniques and different scale-resolution levels, an assessment of temporal-spatial changes of the mangrove peninsula and the adjacent rural socioeconomic impact area, the type of mangrove structure, as well as a land-use cover analyses was undertaken. The definition of the spatial level of detail was found to be a major issue in the development of the GIS, as well as during the processing and analysis procedures. A division between strong and weak patterns in the mangrove ecosystem could be made, which implies different management measures and sets of specific interdisciplinary studies and monitoring at hierarchical scales.

Object-Based Approach for Multi-Scale Mangrove Composition Mapping Using Multi-Resolution Image Datasets

“…The results showed that the developed rule set was able to map targeted mangrove composition objects from images with different spatial resolutions. Only limited studies have implemented the explicit hierarchical model of objects in mangrove mapping [9,12,16,69]. This study demonstrated the effectiveness of having a conceptual hierarchical model for mangrove mapping.…”

Object-Based Image Analysis in Wetland Research: A Review

“…These included peer-reviewed journal articles, conference papers and chapters of book and PhD thesis publications. This review specifically focused on vegetated wetlands (i.e., colonized by aquatic macrophytes) of diverse types [36] such as fresh-and salt-water estuarine, riverine, lacustrine, palustrine and selected marine (mangrove) ecosystems (Table 1, [5][6][7][8]12,13,[15][16][17][18][22][23][24][25][26][27][28][29][30]32,34,) and excluded studies of solely deepwater and open-water aquatic ecosystems such as seagrass beds. The OBIA applications and main research objectives fell into several broad groups (with some papers applicable to more than one of these):…”

“…In OBIA, the images are first segmented into "objects" that are groups of pixels representing ground patches, entities or their elements (primitives) which subsequently can be classified into categories of interest by unsupervised, supervised or rule-based algorithms [14,19,20]. The key benefits of OBIA relative to pixel-based methods include: (1) the possibility to incorporate object-level shape, texture and relevant contextual variables into classification, in addition to spectral values of the input image layers [19,20]; (2) smoothing some of the local variation within objects, which may reduce the salt-and-pepper noise and enhance classification accuracy [13,17,21,22]; and (3) accounting for the landscape hierarchy of patch, cover type and ecosystem structure by working with multiple object layers nested within each other at different spatial scales [23][24][25][26]. The approximation of ground entities and patches by image objects makes them more ecologically relevant and potentially more resilient to minor geospatial positioning and image registration error than pixel units [5,27].…”

Multiple Stable States and Catastrophic Shifts in Coastal Wetlands: Progress, Challenges, and Opportunities in Validating Theory Using Remote Sensing and Other Methods

“…Remote sensing imagery has been used to map coastal topography and flooding [56,63,[82][83][84][85][86] and to map physiological responses of vegetation to salinity or pollution [87][88][89][90]. Some studies have used remote sensing to map coastal or vegetation change over time at two, or a few, time points [91][92][93][94][95][96][97], including analyses of effects of invasive species [59,98]. However, mapping vegetation or topography at even a few points in time provides insufficient evidence to validate the theoretical dynamic equilibria, oscillations, or rapid state changes that would characterize systems truly exhibiting multiple stable states.…”