Edge and fine detail preservation in SAR images through speckle reduction with an adaptive mean filter

A speckle reduction algorithm, the Edge Map‐Directed Adaptive Mean (EMDAM) filter, is studied in this paper. It adapts the ordinary mean filter according to the scene heterogeneity. Edge‐crossing maps determined by an edge detector are used to find the largest homogeneous subregion in the moving filter window. Then, the mean filter is adapted only to this homogeneous part of the moving filter window and applied if no edge crossing is found. We compared some filters in the literature to the EMDAM filter using two examples: a 1997 JERS‐1 synthetic aperture radar (SAR) image of Tuzla, Istanbul and a computer‐simulated SAR image. The filter performance was assessed both quantitatively and qualitatively. We found that the EMDAM filter preserves textures and details while reducing speckle to a desired level. A new testing quantity, the Quality Factor (Q), is also introduced.     

Long and short‐term assessment of surface area changes in saline and freshwater lakes via remote sensing

Advances in remote sensing technology enable monitoring and detection of these vulnerable water bodies that bear numerous functions and ecological services beyond their intended use. As such, valuable data and information may be provided for long and short‐term analyses and stored in a database for future projections. This paper initially grouped 18 natural lakes of the Konya Closed Basin of Turkey according to their salinity level. Freshwater, saline and brackish lakes have then undergone temporal analysis for every 5‐year intervals via Landsat satellite images. Freshwater lake surfaces have not changed noticeably during the inspection period; however, saline waters have decreased in surface area by 32%. Beysehir Lake constituting 94% of the freshwater category and Tuz Lake representing 97% of the saline group were selected for the short‐term analysis that was monthly conducted for years 2017 and 2018 with optical and SAR images to better verify cause and effect relationship.     

MTF driven adaptive multiscale bilateral filtering for pansharpening

The recently proposed Bilateral Filter Luminance Proportional (BFLP) method extracts the high-frequency details from panchromatic (Pan) image via a multiscale bilateral filter and adds them proportionally to the multispectral (MS) image. Although this approach seems similar to other multiresolution (MRA) based schemes such as Additive Wavelet proportional Luminance (AWLP) or Generalized Laplacian (GLP) methods, multiscale bilateral filter obtains the detail planes to be injected to MS image by the combination of two Gaussian kernels controlling the transfer of details and performing successively in spatial and range domains, thus it has two parameters to be defined, namely spatial and range parameters. Since the parameter determination step considerably affects the efficiency of the method, in this paper we propose a single parameter bilateral filter by approximating the Gaussian kernel with the bicubic kernel of à trous wavelet transform (ATWT) or modulation transfer function (MTF). Moreover, we adopt an adaptive injection scheme where the range parameter is determined adaptively so as to follow the statistics of the images to be fused. The pansharpening results are compared with ATWT-based methods, as well as some state-of-the-art methods and BFLP. The visual and quantitative comparisons for Système Pour l’Observation de la Terre 7 (SPOT 7) and Pléiades 1A images, field studies supported with UAV (Unmanned Aerial Vehicle) images and digitization results of the chosen areas in Istanbul Technical University (ITU) Maslak campus confirm the superiority of the proposed detail injection approach.     

Land use change analysis of Beykoz-Istanbul by means of satellite images and GIS.

Management and planning of the natural environment requires spatially accurate and timely information on land use patterns. With repetitive satellite coverage, the rapid evolution of computer technology and the integration of satellite and spatial data, the development of land use applications have become ubiquitous. The integration of Remote Sensing (RS) and Geographic Information Systems (GIS) has been widely applied and recognized as a powerful and effective tool in detecting land use change in urban areas. This paper presents the land use change analysis of the Beykoz region, which is the second largest administrative district of Istanbul. Land use changes and their impacts are monitored using Landsat (MSS - TM) and Spot 5 satellite data in the period of 1975-2001. The independent classification of each satellite image was used as a change analysis method and the resulting images were analyzed with GIS techniques. The results showed that forest area of Beykoz decreased from 80.55% to 70.5% between 1975 and 1984 and during the 1984-2001 periods, the forested area decreased from 70.5% to 68.86% and the urban growth rate was 4.65%.