Spatial heterogeneity in mangroves assessed by GeoEye-1 satellite data: a case-study in Zhanjiang Mangrove National Nature Reserve (ZMNNR), China

Abstract

Abstract. Mangrove forests, which are declining across the globe mainly because of human intervention, require an evaluation of their past and present status (e.g. areal extent, species-level distribution, etc.) to better implement conservation and management strategies. In this paper, mangrove cover dynamics at Gaoqiao (under the jurisdiction of Zhanjiang Mangrove National Nature Reserve – ZMNNR, P. R. China) were assessed through time using 1967 (Corona KH-4B), 2000 (Landsat ETM+), and 2009 (GeoEye-1) satellite imagery. An important decline in mangrove cover (−36%) was observed between 1967 and 2009 due to dike construction for agriculture (paddy) and aquaculture practices. Moreover, dike construction prevented mangroves from expanding landward. Although a small increase of mangrove area was observed between 2000 and 2009 (+24%), the ratio mangrove/aquaculture kept decreasing due to increased aquaculture at the expense of rice culture. In the land-use/cover map based on ground-truth data (5 m × 5 m plot-based tree measurements) (August–September, 2009) and spectral reflectance values (obtained from pansharpened GeoEye-1), both Bruguiera gymnorrhiza and small Aegiceras corniculatum are distinguishable at 73–100% accuracy, whereas tall A. corniculatum is identifiable at only 53% due to its mixed vegetation stands close to B. gymnorrhiza (classification accuracy: 85%). Sand proportion in the sediment showed significant differences (Kruskal-Wallis/ANOVA, P < 0.05) between the three mangrove classes (B. gymnorrhiza and small and tall A. corniculatum). Distribution of tall A. corniculatum on the convex side of creeks and small A.corniculatum on the concave side (with sand) show intriguing patterns of watercourse changes. Overall, the advantage of very high resolution satellite images like GeoEye-1 for mangrove spatial heterogeneity assessment and/or species-level discrimination is well demonstrated, along with the complexity to provide a precise classification for non-dominant species (e.g. Kandelia obovata) at Gaoqiao. Despite the limitations such as geometric distortion and single band information, the 42-yr old Corona declassified images are invaluable for land-use/cover change detections when compared to recent satellite data sets.