The Challenges of Processing Kite Aerial Photography Imagery with Modern Photogrammetry Techniques

Kite Aerial Photography (KAP) is a traditional method of collecting small-format aerial photography used for work in a variety of fields. This research explored techniques for processing KAP imagery with a focus on some of the challenges specific to photo processing. The performance of multiple automated image compositing programs was compared using a common set of 29 images. Those packages that were based on a photogrammetry approach outperformed the non-photogrammetric software, and generated similar levels of quality to one another. While all three photogrammetric packages produced satisfactory output, each had unique challenges

Recent Advances in Image Restoration with Applications to Real World Problems

In the past few decades, imaging hardware has improved tremendously in terms of resolution, making widespread usage of images in many diverse applications on Earth and planetary missions. However, practical issues associated with image acquisition are still affecting image quality. Some of these issues such as blurring, measurement noise, mosaicing artifacts, low spatial or spectral resolution, etc. can seriously affect the accuracy of the aforementioned applications. This book intends to provide the reader with a glimpse of the latest developments and recent advances in image restoration, which includes image super-resolution, image fusion to enhance spatial, spectral resolution, and temporal resolutions, and the generation of synthetic images using deep learning techniques. Some practical applications are also included

Web applications development to support remote sensing methods in open source software

123 σ.Η ανάπτυξη γεωχωρικού λογισμικού ανοιχτού κώδικα τα τελευταία χρόνια έχει γνωρίσει μεγάλη ανάπτυξη. Ο λόγος για αυτό είναι η ύπαρξη των οργανισμών OGC και OpenGeo, οι οποίοι έχουν προτυποποιήσει έναν τρόπο να παρουσιάζονται και να μοιράζονται τα γεωχωρικά δεδομένα στο διαδίκτυο. Καρπός αυτής της ανάπτυξης ήταν μεταξύ άλλων και ο Geoserver, ο οποίος ενσωματώνει GIS επεξεργασίες σε έναν χωρικό server κάτω από το μανδύα του server ανοιχτού κώδικα Tomcat. Στόχος της παρούσας διπλωματικής εργασίας είναι η ανάπτυξη μεθόδων τηλεπισκόπησης σε γλώσσα Java και η χρήση αυτών των εφαρμογών για την επέκταση του Geoserver. Επίσης επιχειρείται να διερευνηθεί κατά πόσο αυτές οι μέθοδοι μπορούν να είναι αξιόπιστες και να συμβάλλουν στην δημιουργία ενός τηλεπισκοπικού σταθμού επεξεργασίας των δεδομένων, ο οποίος να αποτελεί επέκταση του Geoserver.Open source geospatial software meets massive growth lately. One of the reasons forhis is the excistance of oranizations such as OGC and OpenGeo, who developed standards for publishng and sharing geospatial data. Cause of this software development was, among others, Geoserver which comes with built-in GIS processes. Aim of the present project is the development of Remote Sensing processes in Java and the expansion of them to be executed in Geoserver. Also is attempted to be invastigated wheter these methods can be trustworthy and could contribute to the creation of a Remote Sensing toolbox built in Geoserver.Λεωνίδας Μ. Παραγιουδάκη

Metrology, agriculture and food: literature quantitative analysis

Great attention has been given in recent years to the relationships between metrology, agriculture, and food. This study aims at providing an analysis of the literature regarding the relationships between metrology, agriculture, and food. The Scopus online database has been used to extract bibliometric data throughout the search string: TITLE-ABS-KEY (Metrology* AND Agriculture* OR Food*), and the VOSviewer bibliometric software was used to visualize results as bubble maps. The novelty character of this perspective paper is to indicate and point out the main research themes/lines addressing the relationships between metrology, agriculture, and food by analyzing: (i) the authors of the published papers; (ii) the type of paper; (iii) the countries and institutions where the research is developed. Bibliometrics allows one to holistically examine entire scientific areas or sub-fields to get new qualitative and quantitative insights. These results represent a useful tool for identifying emerging research directions, collaboration networks, and suggestions for more in-depth literature searches.This research received no external funding.info:eu-repo/semantics/publishedVersio

HICF: A MATLAB PACKAGE FOR HYPERSPECTRAL IMAGE CLASSIFICATION AND FUSION FOR EDUCATIONAL LEARNING AND RESEARCH

A significant surge has been observed with the development and research in remote sensing in recent years for hyperspectral applications in Earth observation. Subsequently, the development of software and tools have also experienced an unprecedented rise, both in research as well as in academia. Although commercial software and tools such as ENVI by ITT Visual Information Solutions, Boulder, CO, USA are available for visualizing and analyzing the hyperspectral images, such software are expensive. Some open source toolboxes such as the MATLAB-based Hyperspectral Image Analysis Toolbox (HIAT) are also available. However, mostly these toolboxes have not been packaged for dissemination and operation without the MATLAB software which is commercial. In this paper, we introduce the Hyperspectral Image Classification and Fusion (HICF) package which is being developed at the Geoinformatics laboratory, Department of Civil Engineering, Indian Institute of Technology Kanpur (IITK) in MATLAB that can be used by standalone installation with an open source supplementary MATLAB compiler. This software is intended to provide a collection of algorithms both conventional and those developed at the Geoinformatics laboratory that utilizes the numerical computing capability of MATLAB for the processing of hyperspectral and multispectral imagery. The HICF software comprises a simple design of the graphical user interface which can be efficiently used particularly for academic purposes

Detection of leaf structures in close-range hyperspectral images using morphological fusion

Close-range hyperspectral images are a promising source of information in plant biology, in particular, for in vivo study of physiological changes. In this study, we investigate how data fusion can improve the detection of leaf elements by combining pixel reflectance and morphological information. The detection of image regions associated to the leaf structures is the first step toward quantitative analysis on the physical effects that genetic manipulation, disease infections, and environmental conditions have in plants. We tested our fusion approach on Musa acuminata (banana) leaf images and compared its discriminant capability to similar techniques used in remote sensing. Experimental results demonstrate the efficiency of our fusion approach, with significant improvements over some conventional methods

Archaeological prospection with corona and wv-3 satellite imagery of the archaeological site of zar tepe (uzbekistan)

Abstract. The use of different data from satellite platforms for archaeological prospecting and remote sensing has been applied since the end of the 20th century. Although the current use of drones with different visible and multispectral sensors for small areas has partially replaced in some cases the use of this type of satellite information due to its higher spatial resolution. The historical importance of satellite imagery is essential to find out about and compare the transformations of the archaeological landscape of the last 60 years since the CORONA satellite program started in 1960. In this paper we propose the evaluation of a proposal for the automation of processes of two photographic reconnaissance correlative satellite programs CORONA (1960-1972), HEXAGON (1971-1986) declassified since 1995 and 2011 respectively, and the commercial satellite WorldView-3 (WV3) (2014) for use in the detection of buried archaeological structures at the archaeological site of Zar Tepe in the southeast of Uzbekistan. This is a site located in the Surkhan Darya region very little known between the first century BC and the fourth century AD. This methodology is part of the IPAEB project (International Pluridisciplinary Archaeological Expedition to Bactria) led by the University of Barcelona, the University of Salamanca and recently in 2019 the University of Zaragoza. IPAEB was started in 2006 in the South of Uzbekistan and is currently trying to explore the urban planning of the Zar Tepe archaeological site and the elements that make up its natural physical environment: evidence of communication routes, smallholdings, irrigation channels, fences and sources of raw materials

Object-Based Area-to-Point Regression Kriging for Pansharpening

Optical earth observation satellite sensors often provide a coarse spatial resolution (CR) multispectral (MS) image together with a fine spatial resolution (FR) panchromatic (PAN) image. Pansharpening is a technique applied to such satellite sensor images to generate an FR MS image by injecting spatial detail taken from the FR PAN image while simultaneously preserving the spectral information of MS image. Pansharpening methods are mostly applied on a per-pixel basis and use the PAN image to extract spatial detail. However, many land cover objects in FR satellite sensor images are not illustrated as independent pixels, but as many spatially aggregated pixels that contain important semantic information. In this article, an object-based pansharpening approach, termed object-based area-to-point regression kriging (OATPRK), is proposed. OATPRK aims to fuse the MS and PAN images at the object-based scale and, thus, takes advantage of both the unified spectral information within the CR MS images and the spatial detail of the FR PAN image. OATPRK is composed of three stages: image segmentation, object-based regression, and residual downscaling. Three data sets acquired from IKONOS and Worldview-2 and 11 benchmark pansharpening algorithms were used to provide a comprehensive assessment of the proposed OATPRK approach. In both the synthetic and real experiments, OATPRK produced the most superior pan-sharpened results in terms of visual and quantitative assessment. OATPRK is a new conceptual method that advances the pixel-level geostatistical pansharpening approach to the object level and provides more accurate pan-sharpened MS images. IEE

Literature review on the integration of ecosystem services in agricultural economic models

Most analytic tools used in assessing gains from investments in agricultural research either fail to take into consideration environmental impacts or, if they do, it is at a very limited level. The CGIAR Research Programs adopt a systems approach and require a fully integrated consideration of biodiversity and ecosystems services (ESS). This document therefore reviews existing methodologies and available data to identify how biodiversity and ESS can be integrated into analyses at multiple scales; households, farms, landscapes, agriculture sector and economy-wide. The literature review is also designed to identify possible synergies between models at different scales to enable a better understanding of trade-offs between agricultural systems, their environment and human well-being