From data to decision-making – experiences in Integrated Earth Observation (IEO)

Within the confines of Earth Observation Scientific Knowledge and Technology Transfer in Hungary (EKAT) titled ESA PECS project we gained forum for utilization of our earth observation (EO) knowledge and possibility for further development of experiences. The project aims the horizontal preparation of Hungary for ESA membership – for a dynamically developing sphere in the common part of science, technology and business. For the efficient transfer and dissemination, we preconceived target groups and principles to reach main take-up points and to open new forums of information exchange. Nowadays, user-friendly service, complex supply and real-validation process all have great importance. Joining units of suitable data choice, entire ingestion–processing chains and ergonomic interfaces can only offer a timely and professional solution for the challenges of industry and business sectors. It has to be clearly seen, that information and communication technologies (ICT) and information control becomes a more and more significant part of EO services.     

Field Measurements of Plant Emissivity Spectra: An Experimental Study on Remote Sensing of Vegetation in the Thermal Infrared Region

Spectral features of plant species in the visible to SWIR (0.4–2.5 μm) region have been studied extensively, but scanty attention has been given to plant thermal infrared (TIR: 4–14 μm) properties. This paper presents preliminary results of a study that was conducted first time in India to measure radiance and emissivity properties of eight plant species in TIR spectral region in the field conditions using a FTIR (Fourier Transform Infrared) field spectroradiometer working in 4–14 μm at an agriculture experimental farm. Several spectral features in the emissivity spectra of plant species were observed that are probably related to the leaf chemical constituents, such as cellulose and xylan (hemicellulose) and structural aspects of leaf surface like abundance of trichomes and texture. Observations and results from the field measurements were supported by the laboratory measurements like biochemical analysis. These preliminary field emissivity measurements of leaves in TIR show that there is useful spectral information that may be detectable by field-based instrument. More detailed field and laboratory measurements are underway to explore this research theme.     

Towards an integral strategy for modelling uncertain geospatial data

This paper endeavours to put the discussion on errors and uncertainties in geographical information systems (GISs) in a more systematic way by examining the strength and weakness of discrete objects and continous fields, the two distinct schools of spatial data modelling. In doing so, it argues that neither discrete objects nor continous fields alone provide objective and complete representations of highly complex geographical phenomena, though there are good reasons for asserting that continuous fields are better suited to modelling spatial dependence, heterogeneity and fuzzines significant in geographical reality than discrete objects. Thus, there seems to be merit in adopting an integrated model incorporating analytical capabilities of fields and generalization functions of objects, for which extended TIN (triangulated irregular network) models along with their duals (Voronoi diagrams) provide a pragmatical solution.     

Recent literature in cartography and geographic information science

Tissot's Indicatrix and regular grids have been used for assessing map projection accuracies. Despite their broad applicability for accuracy assessment, they have limitations in quantifying resampling errors caused by map projections. This is due to the structural uncertainty with regard to the placement and pattern of grids. It is also difficult to calculate the absolute amount of resampling error in each projection. As an alternative to traditional testing methods, the use of random points was investigated. Specifically, random point generation, resampling with spherical block search algorithms, resampling accuracy with a perfect grid, and resampling accuracy with eight projections were investigated and are discussed here. Eight global referencing methods were tested: the equal-area cylindrical, sinusoidal, Mollweide, Eckert IV, Hammer-Aitoff, interrupted Goode homolosine, integerized sinusoidal projections, and the equal area global gridding with a fixed latitudinal metric distance. The resampling accuracy with a perfect grid is about 75 percent. Results showed the sinusoidal and the integerized sinusoidal projections and equal-area global gridding to achieve the highest accuracies.     

MAPIT: A Computer Program for Production of Flow Maps,Dot Maps and Graduated Symbol Maps

Abstract

This paper describes some results of an attempt to design and to write a general purpose computer program which can be used to produce quality maps of discrete data by the person who has had no training in computer programming. In the first section, the variety of the maps this program can produce is illustrated; in the second section, some of the principles involved in such map production are discussed; in the third section, the input arrangements for using the program are described and, finally, the role of such programs in teaching and research in the years ahead is discussed.     

Simple Approaches to Oil Spill Detection Using Sentinel Application Platform (SNAP)-Ocean Application Tools and Texture Analysis: A Comparative Study

Effective and efficient monitoring of oil spills that originate from ships, offshore platforms and any accidents are of immense importance from the viewpoint of public safety and environmental protection. Detection of spilled oil is also essential to estimate the potential spread and drift from the source to the nearby coastal areas. In this regard, utilization of SAR data for the detection and monitoring of oil spills has received considerable attention in recent times, due to their wide area coverage, day-night and all-weather capabilities. In this paper, two oil spills incidents along the coast of Mumbai, India are investigated; (1) The 2010 oil spill that occurred after the MV MSC Chitra and MV Khalijia-3 collided and (2) the oil spill caused due to sinking of MV RAK carrier in 2011. Two simple and relatively quick approaches for oil spill detection have been applied to VV polarized Radarsat-2 imagery of the incidents and a comparison is made of the results obtained. The first approach utilizes the oil spill detection tool of Sentinel Application Platform (SNAP) and the second explores texture analysis using Grey Level co-occurrence matrix (GLCM). The results of the study show that texture analysis proves to be an efficient method for oil spill detection as compared to the SNAP oil spill detection tool. Nevertheless, both the proposed methodologies are useful for detection of oil spills and for subsequent utilization of the results, timely and cost effectively, for the calibration and validation of numerical models that predict oil spill dispersion trajectories.     

Landscape transform and spatial metrics for mapping spatiotemporal land cover dynamics using Earth Observation data-sets

Analysis of Earth observation (EO) data, often combined with geographical information systems (GIS), allows monitoring of land cover dynamics over different ecosystems, including protected or conservation sites. The aim of this study is to use contemporary technologies such as EO and GIS in synergy with fragmentation analysis, to quantify the changes in the landscape of the Rajaji National Park (RNP) during the period of 19 years (1990–2009). Several statistics such as principal component analysis (PCA) and spatial metrics are used to understand the results. PCA analysis has produced two principal components (PC) and explained 84.1% of the total variance, first component (PC1) accounted for the 57.8% of the total variance while the second component (PC2) has accounted for the 26.3% of the total variance calculated from the core area metrics, distance metrics and shape metrics. Our results suggested that notable changes happened in the RNP landscape, evidencing the requirement of taking appropriate measures to conserve this natural ecosystem.     

A comparative analysis of pansharpening techniques on QuickBird and WorldView-3 images

Nowadays, different image pansharpening methods are available, which combine the strengths of different satellite images that have different spectral and spatial resolutions. These different image fusion methods, however, add spectral and spatial distortions to the resultant images depending on the required context. Therefore, a careful selection of the fusion method is required. Simultaneously, it is also essential that the fusion technique should be efficient to cope with the large data. In this paper, we investigated how different pansharpening algorithms perform, when applied to very high-resolution WorldView-3 and QuickBird satellite images effectively and efficiently. We compared these 27 pansharpening techniques in terms of quantitative analysis, visual inspection and computational complexity, which has not previously been formally tested. In addition, 12 different image quality metrics available in literature are used for quantitative analysis purpose.     

Analysis of urban built-up areas and surface urban heat island using downscaled MODIS derived land surface temperature data

Regional scale urban built-up areas and surface urban heat islands (SUHI) are important for urban planning and policy formation. Owing to coarse spatial resolution (1000 m), it is difficult to use Moderate Resolution Imaging Spectroradiometer (MODIS) Land surface temperature (LST) products for mapping urban areas and visualization, and SUHI-related studies. To overcome this problem, the present study downscaled MODIS (1000 m resolution)-derived LST to 250 m resolution to map and visualize the urban areas and identify the basic components of SUHI over 12 districts of Punjab, India. The results are compared through visual interpretation and statistical procedure based on similarity analysis. The increased entropy value in the downscaled LST signifies higher information content. The temperature variation within the built-up and its environs is due to difference in land use and is depicted better in the downscaled LST. The SUHI intensity analysis of four cities (Ludhiana, Patiala, Moga and Vatinda) indicates that mean temperature in urban built-up core is higher (38.87 °C) as compared to suburban (35.85 °C) and rural (32.41 °C) areas. The downscaling techniques demonstrated in this paper enhance the usage of open-source wide swath MODIS LST for continuous monitoring of SUHI and urban area mapping, visualisation and analysis at regional scale. Such initiatives are useful for the scientific community and the decision-makers.