Exploiting Deep Features for Remote Sensing Image Retrieval: A Systematic Investigation

Remote sensing (RS) image retrieval is of great significant for geological information mining. Over the past two decades, a large amount of research on this task has been carried out, which mainly focuses on the following three core issues: feature extraction, similarity metric and relevance feedback. Due to the complexity and multiformity of ground objects in high-resolution remote sensing (HRRS) images, there is still room for improvement in the current retrieval approaches. In this paper, we analyze the three core issues of RS image retrieval and provide a comprehensive review on existing methods. Furthermore, for the goal to advance the state-of-the-art in HRRS image retrieval, we focus on the feature extraction issue and delve how to use powerful deep representations to address this task. We conduct systematic investigation on evaluating correlative factors that may affect the performance of deep features. By optimizing each factor, we acquire remarkable retrieval results on publicly available HRRS datasets. Finally, we explain the experimental phenomenon in detail and draw conclusions according to our analysis. Our work can serve as a guiding role for the research of content-based RS image retrieval

Development and Application of Operational Techniques for the Inventory and Monitoring of Resources and Uses for the Texas Coastal Zone

There are no author-identified significant results in this report

Application of LANDSAT to the surveillance of lake eutrophication in the Great Lakes basin

The author has identified the following significant results. A step-by-step procedure for establishing and monitoring the trophic status of inland lakes with the use of LANDSAT data, surface sampling, laboratory analysis, and aerial observations were demonstrated. The biomass was related to chlorophyll-a concentrations, water clarity, and trophic state. A procedure was developed for using surface sampling, LANDSAT data, and linear regression equations to produce a color-coded image of large lakes showing the distribution and concentrations of water quality parameters, causing eutrophication as well as parameters which indicate its effects. Cover categories readily derived from LANDSAT were those for which loading rates were available and were known to have major effects on the quality and quantity of runoff and lake eutrophication. Urban, barren land, cropland, grassland, forest, wetlands, and water were included

Technical approaches, chapter 3, part E

Radar altimeters, scatterometers, and imaging radar are described in terms of their functions, future developments, constraints, and applications

Volcanic Hot-Spot Detection Using SENTINEL-2: A Comparison with MODIS−MIROVA Thermal Data Series

In the satellite thermal remote sensing, the new generation of sensors with high-spatial resolution SWIR data open the door to an improved constraining of thermal phenomena related to volcanic processes, with strong implications for monitoring applications. In this paper, we describe a new hot-spot detection algorithm developed for SENTINEL-2/MSI data that combines spectral indices on the SWIR bands 8a-11-12 (with a 20-meter resolution) with a spatial and statistical analysis on clusters of alerted pixels. The algorithm is able to detect hot-spot-contaminated pixels (S2Pix) in a wide range of environments and for several types of volcanic activities, showing high accuracy performances of about 1% and 94% in averaged omission and commission rates, respectively, underlining a strong reliability on a global scale. The S2-derived thermal trends, retrieved at eight key-case volcanoes, are then compared with the Volcanic Radiative Power (VRP) derived from MODIS (Moderate Resolution Imaging Spectroradiometer) and processed by the MIROVA (Middle InfraRed Observation of Volcanic Activity) system during an almost four-year-long period, January 2016 to October 2019. The presented data indicate an overall excellent correlation between the two thermal signals, enhancing the higher sensitivity of SENTINEL-2 to detect subtle, low-temperature thermal signals. Moreover, for each case we explore the specific relationship between S2Pix and VRP showing how different volcanic processes (i.e., lava flows, domes, lakes and open-vent activity) produce a distinct pattern in terms of size and intensity of the thermal anomaly. These promising results indicate how the algorithm here presented could be applicable for volcanic monitoring purposes and integrated into operational systems. Moreover, the combination of high-resolution (S2/MSI) and moderate-resolution (MODIS) thermal timeseries constitutes a breakthrough for future multi-sensor hot-spot detection systems, with increased monitoring capabilities that are useful for communities which interact with active volcanoes

Analyses of the cloud contents of multispectral imagery from LANDSAT 2: Mesoscale assessments of cloud and rainfall over the British Isles

The author has identified the following significant results. It was demonstrated that satellites with sufficiently high resolution capability in the visible region of the electromagnetic spectrum could be used to check the accuracy of estimates of total cloud amount assessed subjectively from the ground, and to reveal areas of performance in which corrections should be made. It was also demonstrated that, in middle latitude in summer, cloud shadow may obscure at least half as much again of the land surface covered by an individual LANDSAT frame as the cloud itself. That proportion would increase with latitude and/or time of year towards the winter solstice. Analyses of sample multispectral images for six different categories of clouds in summer revealed marked differences between the reflectance characteristics of cloud fields in the visible/near infrared region of the spectrum

Horizontal accuracy assessment of very high resolution Google Earth images in the city of Rome, Italy

Google Earth (GE) has recently become the focus of increasing interest and popularity among available online virtual globes used in scientific research projects, due to the free and easily accessed satellite imagery provided with global coverage. Nevertheless, the uses of this service raises several research questions on the quality and uncertainty of spatial data (e.g. positional accuracy, precision, consistency), with implications for potential uses like data collection and validation. This paper aims to analyze the horizontal accuracy of very high resolution (VHR) GE images in the city of Rome (Italy) for the years 2007, 2011, and 2013. The evaluation was conducted by using both Global Positioning System ground truth data and cadastral photogrammetric vertex as independent check points. The validation process includes the comparison of histograms, graph plots, tests of normality, azimuthal direction errors, and the calculation of standard statistical parameters. The results show that GE VHR imageries of Rome have an overall positional accuracy close to 1 m, sufficient for deriving ground truth samples, measurements, and large-scale planimetric maps

Scale and texture in digital image classification

This thesis is a theoretical and empirical study on textural properties of digital images. Spatial information exists at a hierarchy of scales and texture is a consequence of the objects in that hierarchy. Within-class texture results from the spatial arrangement of objects at the next finer level in the hierarchy than the informational class. Between-class texture results from spectral differences between adjacent classes and is most obvious near class edges, especially for smooth classes. In rough classes between-class variance may not differ much from within-class variance. Errors in classifications using texture, therefore, are most likely associated with, class edges; however, investigators often avoid edges in evaluating texture or classification.;The window sizes needed to produce a stable texture measure are often large. Experiments with ADAR 1-meter data suggest that windows of 50 to 300 meters are necessary. Small windows are required to minimize edge effects. This is inherently contradictory as windows used to produce stable texture measures also produce a large edge effect.;Experiments with simulated data showed that separability of classes increased when texture was used in addition to spectral information. Separability of texture also improved with larger scale windows. This improvement was over-estimated when pixels were chosen away from class edges. The ADAR data showed that separability of the interiors of classes improved with the addition of texture, but for the class as a whole, the class separability actually fell. Maximum Likelihood classification of the ADAR data demonstrated the effect of edges and multiple scales in reducing the accuracy of classification incorporating texture

A Field Survey and Geographical Information Systems (GIS) Based Investigation of the Archaeological Landscape in the Niger River Valley, Republic of Benin

Abstract The Niger River Valley in the Republic of Benin is an archaeologically rich landscape, where hundreds of sites line the river’s tributaries. Before this doctoral research was conducted in the region, the landscape here was a terra-incognita. In order to archaeologically investigate the area, several methods were used consisting of a field walking survey, and the use of satellite remote sensing and Geographical Information Systems (GIS). An integration of these methods, which are commonly used in research out of Africa, showed the diverse nature of archaeology in this region. The field walking survey revealed the position of over 300 sites and around 50,000 material culture artefacts, comprising of mainly ceramic vessel sherds. The field survey was undertaken over 45 days and covered a total area of 25km2 within four geographical zones in the study area. A comprehensive gazetteer was produced from the data collected. Remote sensing methods that manipulate multispectral satellite imagery were used to identify sites from the air, because the archaeology of this region is not visible from standard air photographs. The mapping of sites using GIS facilitated in establishing fundamental landscape patterns, which helped substantiate theories surrounding West African urbanism and human-environment interactions. The results conveyed that settlements in this region favour areas where water is available, mainly close to perennial and ephemeral fluvial systems. Furthermore, the archaeological sites identified display strong evidence of spatial clustering, which has been shown in other West African contexts to be indicative of early urbanisation