Mapping marine biocenoses is an efficient method for providing useful data for the management and conservation of Mediterranean lagoons. Fused images from two satellites, SPOT 5 and IKONOS, were tested as management tools for identifying specific ecosystems in the El Bibane lagoon, situated in southern Tunisia near the Libyan border. The objectives of this study were to provide a precise map of the entire El Bibane lagoon using fused images from SPOT 5 and to compare fused images from SPOT 5 and IKONOS over a test-area. After applying a supervised classification, pixels are automatically classified in four classes: low seagrass cover, high seagrass cover, superficial mobile sediments and deep mobile sediments. The maps of the lagoon revealed and confirmed an extremely wide distribution of seagrass meadows within the lagoon (essentially Cymodocea nodosa; 19 546 ha) and a large area of mobile sediments more or less parallel to the shore (3 697 ha). A direct comparison of overall accuracy between SPOT 5 over the entire area, SPOT 5 over the test-area and IKONOS over the test-area revealed that these tools provided accurate mapping of the lagoon environment (83.25%, 85.91% and 73.41% accuracy, respectively). The SPOT 5 images provided greater overall accuracy than the IKONOS image, but did not take into account the heterogeneous spatial structure of the seagrasses and sediments present in the lagoon environment. Although IKONOS imagery provided lower overall accuracy than SPOT 5, it proved a very useful tool for the mapping of heterogeneous structures as it enabled the patchiness of formations to be better taken into account. The use of SPOT 5 and IKONOS fused images appears to be very promising for completing the mapping of lagoons in other regions and countries of the Mediterranean Sea. 相似文献
We analyzed the spatial local accuracy of land cover (LC) datasets for the Qiangtang Plateau, High Asia, incorporating 923 field sampling points and seven LC compilations including the International Geosphere Biosphere Programme Data and Information System (IGBPDIS), Global Land cover mapping at 30 m resolution (GlobeLand30), MODIS Land Cover Type product (MCD12Q1), Climate Change Initiative Land Cover (CCI-LC), Global Land Cover 2000 (GLC2000), University of Maryland (UMD), and GlobCover 2009 (Glob-Cover). We initially compared resultant similarities and differences in both area and spatial patterns and analyzed inherent relationships with data sources. We then applied a geographically weighted regression (GWR) approach to predict local accuracy variation. The results of this study reveal that distinct differences, even inverse time series trends, in LC data between CCI-LC and MCD12Q1 were present between 2001 and 2015, with the exception of category areal discordance between the seven datasets. We also show a series of evident discrepancies amongst the LC datasets sampled here in terms of spatial patterns, that is, high spatial congruence is mainly seen in the homogeneous southeastern region of the study area while a low degree of spatial congruence is widely distributed across heterogeneous northwestern and northeastern regions. The overall combined spatial accuracy of the seven LC datasets considered here is less than 70%, and the GlobeLand30 and CCI-LC datasets exhibit higher local accuracy than their counterparts, yielding maximum overall accuracy (OA) values of 77.39% and 61.43%, respectively. Finally, 5.63% of this area is characterized by both high assessment and accuracy (HH) values, mainly located in central and eastern regions of the Qiangtang Plateau, while most low accuracy regions are found in northern, northeastern, and western regions.
