Comprehensive investigation on non-parametric classification methods in order to separate urban objects using the integration of very high spatial resolution LiDAR and aerial data

2017 ◽  
Vol 5 (3) ◽  
pp. 77-97
Author(s):  
Zinat Ghavami ◽  
Hossein Arefi ◽  
Behnaz Bigdeli ◽  
Milad Janalipour ◽  
◽  
...  
Keyword(s):  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Classification Methods ◽  
Comprehensive Investigation ◽  
Very High Spatial Resolution ◽  
Parametric Classification ◽  
Very High ◽  
Non Parametric

scholarly journals High spatial resolution photo mosaicking for the monitoring of coralligenous reefs

Coral Reefs ◽  
2021 ◽  
Author(s):  
E. Casoli ◽  
D. Ventura ◽  
G. Mancini ◽  
D. S. Pace ◽  
A. Belluscio ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Low Cost ◽  
Pixel Resolution ◽  
Recording Apparatus ◽  
Assemblage Composition ◽  
Very High Spatial Resolution ◽  
Vertical Walls ◽  
Non Destructive ◽  
Very High

AbstractCoralligenous reefs are characterized by large bathymetric and spatial distribution, as well as heterogeneity; in shallow environments, they develop mainly on vertical and sub-vertical rocky walls. Mainly diver-based techniques are carried out to gain detailed information on such habitats. Here, we propose a non-destructive and multi-purpose photo mosaicking method to study and monitor coralligenous reefs developing on vertical walls. High-pixel resolution images using three different commercial cameras were acquired on a 10 m2 reef, to compare the effectiveness of photomosaic method to the traditional photoquadrats technique in quantifying the coralligenous assemblage. Results showed very high spatial resolution and accuracy among the photomosaic acquired with different cameras and no significant differences with photoquadrats in assessing the assemblage composition. Despite the large difference in costs of each recording apparatus, little differences emerged from the assemblage characterization: through the analysis of the three photomosaics twelve taxa/morphological categories covered 97–99% of the sampled surface. Photo mosaicking represents a low-cost method that minimizes the time spent underwater by divers and capable of providing new opportunities for further studies on shallow coralligenous reefs.

scholarly journals Mapping Urban Functional Zones by Integrating Very High Spatial Resolution Remote Sensing Imagery and Points of Interest: A Case Study of Xiamen, China

2018 ◽  
Vol 10 (11) ◽  
pp. 1737 ◽  
Author(s):  
Jinchao Song ◽  
Tao Lin ◽  
Xinhu Li ◽  
Alexander V. Prishchepov
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Remote Sensing Images ◽  
Remote Sensing Imagery ◽  
Points Of Interest ◽  
Very High Spatial Resolution ◽  
Functional Zones ◽  
Very High

Fine-scale, accurate intra-urban functional zones (urban land use) are important for applications that rely on exploring urban dynamic and complexity. However, current methods of mapping functional zones in built-up areas with high spatial resolution remote sensing images are incomplete due to a lack of social attributes. To address this issue, this paper explores a novel approach to mapping urban functional zones by integrating points of interest (POIs) with social properties and very high spatial resolution remote sensing imagery with natural attributes, and classifying urban function as residence zones, transportation zones, convenience shops, shopping centers, factory zones, companies, and public service zones. First, non-built and built-up areas were classified using high spatial resolution remote sensing images. Second, the built-up areas were segmented using an object-based approach by utilizing building rooftop characteristics (reflectance and shapes). At the same time, the functional POIs of the segments were identified to determine the functional attributes of the segmented polygon. Third, the functional values—the mean priority of the functions in a road-based parcel—were calculated by functional segments and segmental weight coefficients. This method was demonstrated on Xiamen Island, China with an overall accuracy of 78.47% and with a kappa coefficient of 74.52%. The proposed approach could be easily applied in other parts of the world where social data and high spatial resolution imagery are available and improve accuracy when automatically mapping urban functional zones using remote sensing imagery. It will also potentially provide large-scale land-use information.

scholarly journals Remote Sensing of Coconut Trees in Tonga Using Very High Spatial Resolution WorldView-3 Data

2020 ◽  
Vol 12 (19) ◽  
pp. 3113 ◽  
Author(s):  
Eric F. Vermote ◽  
Sergii Skakun ◽  
Inbal Becker-Reshef ◽  
Keiko Saito
Keyword(s):  
Spatial Resolution ◽  
Near Infrared ◽  
Census Data ◽  
High Spatial Resolution ◽  
Sampling Rate ◽  
Validation Data ◽  
Geometrical Properties ◽  
Coconut Tree ◽  
Very High Spatial Resolution ◽  
Very High

This paper presents a simple and efficient image processing method for estimating the number of coconut trees in the Tonga region using very high spatial resolution data (30 cm) in the blue, green, red and near infrared spectral bands acquired by the WorldView-3 sensor. The method is based on the detection of tree shadows and the further analysis to reject false detection using geometrical properties of the derived segments. The algorithm is evaluated by comparing coconut tree counts derived by an expert through photo-interpretation over 57 randomly distributed (4% sampling rate) segments of 200 m × 200 m over the Vaini region of the Tongatapu island. The number of detected trees agreed within 5% versus validation data. The proposed method was also evaluated over the whole Tonga archipelago by comparing satellite-derived estimates to the 2015 agricultural census data—the total tree counts for both Tonga and Tongatapu agreed within 3%.

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