Studies on microwave remote sensing data in conjunction with optical data for land use/land cover mapping and assessment

Abstract

The operational capability of optical sensors are limited under cloud cover conditions and alternatively the all weather capability of sensors operating in microwave region play an important role in a tropical country like India where the persistence of cloud cover is high. This paper deals with the evaluation of ERS-1 Synthetic Aperture Radar (SAR) data in conjunction with Indian Remote Sensing Data (IRS) LISS-II optical data in synergistic combinations with microwave data for land use/land cover mapping and assessment. Here part of East Godavari District of Andhra Pradesh, India covering coringa reserved forest and Kakinada town and its surroundings covering 1900 sq.kms of area has been considered for the study. The area selected encompasses a variety of land use/land cover features like urban areas, croplands, plantations, mangroves, marshy and waterlogged areas, salt pans, waterbodies and aquaculture sites. The data from coherent imaging systems like SAR are corrupted with speckle noise and in order to minimise speckle different filtering techniques have been applied on SAR raw data. It has been observed that the 5x5 median filter could adequately minimise the speckle interference in feature delineation. Land use/land cover maps have been generated from raw and filtered SAR data sets and also the mapping accuracy has been estimated using Kappa and proportional accuracy statistical methods. The increased mapping accuracy in filtered SAR data has been attributed essentially to reduction of speckle noise. False color composites (FCC) of different combinations of filtered and registered data products of LISS-II and SAR data have been generated. Intensity-Hue Saturation (IHS) transformation and Principal Component Analysis have been applied to the registered data sets. Ranking table quantifying advantages of different combinations has beenprepared. From the analysis, it has been concluded that synergistic combination of optical and microwave data helps in delineating land use/land cover categories upto Level-III compared to individual data sets.

Comparison of Sensor Fusion Methods for Land Cover Delineations

“…This study extends sensor fusion results from previous studies by these authors and others (Brisco and Brown, 1998;Raghavswamy et al, 1996;Pohl and Downloaded by [University of Chicago Library] at 02:41 03 October 2014 Van Genderen, 1998;Haack and Bechdol, 2000;Nyoungui et al, 2000;Malcom et al, 2001). One of these data sets, Wad Medani, has been examined using a parallelepiped decision rule and only the original data without any modification of radar either spatially or radiometrically (Haack and Slonecker, 1994).…”

“…A problem with these systems is that spectral responses in the optical wavelengths are sensitive to differential scattering and absorption caused by chlorophyll, green leaf area, and leaf structure, leaving some vegetation types that cannot be separated due to the similarity of their spectral responses (Raghavswamy et al, 1996). Active microwave energy of radar responds to different terrain and dielectric factors, such as plant canopy roughness and structure, plant moisture content, and subcanopy conditions.…”

Automated global water mapping based on wide-swath orbital synthetic-aperture radar

“…In contrast, and although not capable of observing through clouds, the MODIS optical sensor on NASA's Terra and Aqua satellites has some important advantages: MODIS visible and near IR (NIR) bands 1 and 2 provide global, twice daily coverage at 250 m spatial resolution, and optical multispectral classification methods may better distinguish land and water in some areas, including in deserts where SAR backscatter may be very low and highly variable (a.o. Ridley et al, 1996;Raghavswamy et al, 2008). The utility of MODIS for flood-related work has been repeatedly demonstrated by maps disseminated from the Dartmouth Flood Observatory (http://floodobservatory.colorado.…”

Quality Assessment of Fused Image of Modis and Palsar

“…These two sensor types are very different in terms of the wavelength of their electromagnetic energy, sensor structure, and image product [3][4][5][6]. In regions with frequent cloud cover the number of suitable optical data is often limited.…”