scholarly journals A Hybrid Model Integrating Spatial Pattern, Spatial Correlation, and Edge Information for Image Classification

2019 ◽  
Vol 11 (13) ◽  
pp. 1599 ◽  
Author(s):  
Yunwei Tang ◽  
Linhai Jing ◽  
Fan Shi ◽  
Xiao Li ◽  
Fang Qiu
Keyword(s):  
Remote Sensing ◽  
Spatial Pattern ◽  
Spatial Correlation ◽  
Hybrid Model ◽  
General Distribution ◽  
Multiple Point ◽  
Spatial Covariance ◽  
Edge Preserving ◽  
Remote Sensing Classification ◽  
Different Sources

This paper develops a novel hybrid model that integrates three spatial contexts into probabilistic classifiers for remote sensing classification. First, spatial pattern is introduced using multiple-point geostatistics (MPGs) to characterize the general distribution and arrangement of land covers. Second, spatial correlation is incorporated using spatial covariance to quantify the dependence between pixels. Third, an edge-preserving filter based on the Sobel mask is introduced to avoid the over-smoothing problem. These three types of contexts are combined with the spectral information from the original image within a higher-order Markov random field (MRF) framework for classification. The developed model is capable of classifying complex and diverse land cover types by allowing effective anisotropic filtering of the image while retaining details near edges. Experiments with three remote sensing images from different sources based on three probabilistic classifiers obtained results that significantly improved classification accuracies when compared with other popular contextual classifiers and most state-of-the-art methods.

scholarly journals Spatial Pattern of Bathymetry in Wangi-Wangi Island and Its Surrounding Based on GEBCO Data and Nautical Map

2016 ◽  
Vol 29 (2) ◽  
pp. 144
Author(s):  
Yulius Yulius ◽  
H L Salim ◽  
M Ramdhan
Keyword(s):  
Remote Sensing ◽  
Spatial Pattern ◽  
Shallow Water ◽  
Spatial Correlation ◽  
Research Area ◽  
Barrier Reef ◽  
Kriging Method ◽  
Gis And Remote Sensing ◽  
Eastern Side ◽  
Gis Technique

The study aims is to define bathymetry based on General Bathymetric Chart of the Oceans (GEBCO) and Nautical Map using GIS technique. The methods used in this study are the kriging method which combines the spatial correlation among the data using GIS and Remote Sensing software. The result shows that bathymetry at research area can be divided into five classes, these are: (1) 0-2 meter with area of 1.797,61 hectare, (2) 2-5 meter with area of 2.059,06 hectare, (3) 5-10 meter with area of 1.184,02 hectare, (4) 10-25 meter with area of 3.025.00 hectare, (5) 25-200 meter with area of 5.648.62 hectare.The spatial pattern of bathymetry dispersed from the shallow water at the edge of beach and more deep at the offshore, except at the eastern side of Wangi-Wangi island which has barrier reef and created basin between them.

A spatial-channel progressive fusion ResNet for remote sensing classification

2020 ◽  
Author(s):  
Hao Zhu ◽  
Mengru Ma ◽  
Wenping Ma ◽  
Licheng Jiao ◽  
Shikuan Hong ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Classification

scholarly journals Using a Groundwater Adjusted Water Balance Approach and Copulas to Evaluate Spatial Patterns and Dependence Structures in Remote Sensing Derived Evapotranspiration Products

2021 ◽  
Vol 13 (5) ◽  
pp. 853
Author(s):  
Mohsen Soltani ◽  
Julian Koch ◽  
Simon Stisen
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
Spatial Pattern ◽  
Spatial Patterns ◽  
Principal Component ◽  
Small Scale ◽  
Dependence Structure ◽  
Test Case ◽  
Catchment Scale ◽  
Balance Approach

This study aims to improve the standard water balance evapotranspiration (WB ET) estimate, which is typically used as benchmark data for catchment-scale ET estimation, by accounting for net intercatchment groundwater flow in the ET calculation. Using the modified WB ET approach, we examine errors and shortcomings associated with the long-term annual mean (2002–2014) spatial patterns of three remote-sensing (RS) MODIS-based ET products from MODIS16, PML_V2, and TSEB algorithms at 1 km spatial resolution over Denmark, as a test case for small-scale, energy-limited regions. Our results indicate that the novel approach of adding groundwater net in water balance ET calculation results in a more trustworthy ET spatial pattern. This is especially relevant for smaller catchments where groundwater net can be a significant component of the catchment water balance. Nevertheless, large discrepancies are observed both amongst RS ET datasets and compared to modified water balance ET spatial pattern at the national scale; however, catchment-scale analysis highlights that difference in RS ET and WB ET decreases with increasing catchment size and that 90%, 87%, and 93% of all catchments have ∆ET < ±150 mm/year for MODIS16, PML_V2, and TSEB, respectively. In addition, Copula approach captures a nonlinear structure of the joint relationship with multiple densities amongst the RS/WB ET products, showing a complex dependence structure (correlation); however, among the three RS ET datasets, MODIS16 ET shows a closer spatial pattern to the modified WB ET, as identified by a principal component analysis also. This study will help improve the water balance approach by the addition of groundwater net in the ET estimation and contribute to better understand the true correlations amongst RS/WB ET products especially over energy-limited environments.

Based on IDRISI Remote Sensing Images Land-Use Types of Supervised Classification Techniques

2013 ◽  
Vol 415 ◽  
pp. 305-308
Author(s):  
Kun Zhang ◽  
Hai Feng Wang ◽  
Zhuang Li
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Classification Techniques ◽  
Analysis And Evaluation ◽  
Remote Sensing Classification ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Remote Sensing Image Classification ◽  
Land Use Types ◽  
Area Distribution

With remote sensing technology and computer technology, remote sensing classification technology has been rapid progress. In the traditional classification of remote sensing technology, based on the combination of today's technology in the field of remote sensing image classification, some new developments and applications for land cover classification techniques to make more comprehensive elaboration. Using the minimum distance classifier extracts of the study area land use types. Ultimately extracted land use study area distribution image and make its analysis and evaluation.

scholarly journals Spatial pattern evaluation of a calibrated national hydrological model – a remote sensing based diagnostic approach

2017 ◽  
Author(s):  
Gorka Mendiguren ◽  
Julian Koch ◽  
Simon Stisen
Keyword(s):  
Remote Sensing ◽  
Spatial Pattern ◽  
Spatial Patterns ◽  
Hydrological Model ◽  
Remote Sensing Data ◽  
Driving Mechanism ◽  
Distributed Hydrological Model ◽  
Eof Analysis ◽  
Sensing Data ◽  
Spatio Temporal

Abstract. Distributed hydrological models are traditionally evaluated against discharge stations, emphasizing the temporal and neglecting the spatial component of a model. The present study widens the traditional paradigm by highlighting spatial patterns of evapotranspiration (ET), a key variable at the land-atmosphere interface, obtained from two different approaches at the national scale of Denmark. The first approach is based on a national water resources model (DK-model), using the MIKE-SHE model code, and the second approach utilizes a two source energy balance model (TSEB) driven mainly by satellite remote sensing data. The main hypothesis of the study is that while both approaches are essentially estimates, the spatial patterns of the remote sensing based approach are explicitly driven by observed land surface temperature and therefore represent the most direct spatial pattern information of ET; enabling its use for distributed hydrological model evaluation. Ideally the hydrological model simulation and remote sensing based approach should present similar spatial patterns and driving mechanism of ET. However, the spatial comparison showed that the differences are significant and indicating insufficient spatial pattern performance of the hydrological model. The differences in spatial patterns can partly be explained by the fact that the hydrological model is configured to run in 6 domains that are calibrated independently from each other, as it is often the case for large scale multi-basin calibrations. Furthermore, the model incorporates predefined temporal dynamics of Leaf Area Index (LAI), root depth (RD) and Crop coefficient (Kc) for each land cover type. This zonal approach of model parametrization ignores the spatio-temporal complexity of the natural system. To overcome this limitation, the study features a modified version of the DK-Model in which LAI, RD, and KC are empirically derived using remote sensing data and detailed soil property maps in order to generate a higher degree of spatio-temporal variability and spatial consistency between the 6 domains. The effects of these changes are analyzed by using the empirical orthogonal functions (EOF) analysis to evaluate spatial patterns. The EOF-analysis shows that including remote sensing derived LAI, RD and KC in the distributed hydrological model adds spatial features found in the spatial pattern of remote sensing based ET.

Sign in / Sign up

Export Citation Format

Share Document