Practical Experiences with Films, Cameras and Navigation Systems

The first author commenced his experiences with aerial photography in 1945, when he joined the Royal Air Force (RAF). The aerial cameras used at that time were the Williamson F24 and F52, with Ilford HP3 and FP3 panchromatic films. Subsequently the Williamson F95 camera was tested against the USAF Sonne 11 camera. During his final years in the RAF, a variety of film types was employed: colour, monochrome infra-red and false colour infra-red. Additional experience was gained when the author was employed by the International Training Centre (ITC), The Netherlands and he saw the further development of the air camera from the Wild RC8 and Zeiss (Oberkochen) RMK 15/23 to the Wild RC20, Zeiss (Jena) LMK and Zeiss (Oberkochen) RMK TOP. He predicts that the future lies with digital cameras.
The second author started working with aerial photography in the 1950s. Details are given of cameras, visual navigation sights and survey aircraft dating from that period. Overseas operations, carried out mainly by Hunting Surveys and Fairey Surveys, posed particular problems because the majority of the work there was undertaken without the aid of existing maps. The introduction of external navigation systems is described, from the Decca ship navigation system, through the GNS-200 VLF/Omega low frequency radio system to INS, the Inertial Navigation System. The author later joined the ITC, which enabled him to participate in trials of the Computer-controlled Photo Navigation System. Eventually practical experience was gained with differential GPS, particularly in countries in southeast Asia. Aerial photography currently appears to benefit less from financial investment than the photographic, aviation and survey industries. However, the satisfaction of making a significant contribution to major overseas development projects outweighs the frustration of lack of acceptance of plans for the future of the air survey industry.     

An analysis of changes in the urban landscape composition and configuration in the Sancaktepe District of Istanbul Metropolitan City,Turkey using landscape metrics and satellite data

Changes in landscape composition and configuration patterns of Sancaktepe Municipal District in the Asian side of Istanbul Metropolitan City of Turkey were analysed using landscape metrics. Class-level and landscape-level metrics were calculated from the land cover/land use data using Patch Analyst, an extension in the Arc View GIS. The land cover/land use data were derived from classified satellite images of Landsat Thematic Mapper of 2002 and 2009 for Sancaktepe District. There was evidence of increase in agglomeration process of built-up patches as indicated by the increases in mean patch size, decrease in total edge and number of patches between 2002 and 2009. The urban expansion pattern experienced overall was not fragmented but concentrated due to infilling around existing patches. Changes in Area-Weighted Mean Shape Index and Area-Weighted Patch Fractal Dimension Index indicated that the physical shapes within built-up, forest and bareland areas were relatively complex and irregular. A conclusion is made in this study that spatial metrics are useful tools to describe the urban landscape composition and configuration in its various aspects and certain decisions whether to approve a specific development in urban planning could, for example, be based on some measures of urban growth form or pattern in terms of uniformity and irregularity, attributable to the dynamic processes of agglomeration and fragmentation of land cover/land use patches caused by urban expansion.     

Comparison of basin morphometry derived from topographic maps,ASTER and SRTM DEMs: an example from Kerala,India

The drainage network of a sixth-order tropical river basin, viz. Ithikkara river basin, was extracted from different sources such as Survey of India topographic maps (1: 50,000; TOPO) and digital elevation data of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) (30 m) and Shuttle Radar Topography Mapping Mission (SRTM) (90 m). Basin morphometric attributes were estimated to evaluate the accuracy of the digital elevation model (DEM)-derived drainage networks for hydrologic applications as well as terrain characterization. The stream networks derived from ASTER and SRTM DEMs show significant agreement (with slight overestimation of lower order streams) with that of TOPO. The study suggests that SRTM (despite the coarser spatial resolution) provides better results, in drainage delineation and basin morphometry, compared to ASTER. Further, the variability of basin morphometry among the data sources might be attributed to spatial variation of elevation, raster grid size and vertical accuracy of the DEMs as well as incapability of the surface hydrologic analysis functions in the GIS platform.     

Semi-automatic delineation of badlands using contrast in vegetation activity: a case study in the lower Chambal valley,India

Population growth worldwide leads to an increasing pressure on the land. Recent studies reported that many areas covered by badlands are decreasing because parts of badlands are being levelled and converted into arable land. It is important to monitor these changes for environmental planning. This paper proposes a remote-sensing-based detection method which allows mapping of badland dynamics based on seasonal vegetation changes in the lower Chambal valley, India. Supervised classification was applied on three Landsat (Thematic Mapper) images, from 3 different seasons; January (winter), April (summer) and October (post-monsoon). Different band selection methods were applied to get the best classification. Validation was done by ground referencing and a GeoEye-1 satellite image. The image from January performed best with overall accuracy of 87% and 0.69 of kappa. This method opens the possibilities of using semi-automatic classification for the Chambal badlands which is so far mapped with manual interpretations only.     

Applying landscape-ecological concept and GIS modelling for assessing and mapping of ecological situation of mountainous landscapes (on the case of Syunik marz,Armenia)

Regional landscape-ecological studies have acquired a special topicality as they assure efficient environmental conservation and sustainable use of natural resources. A landscape-ecological analysis was performed based on four basic integral indices: (1) ecological potential, (2) ecological stability, (3) ecological load and (4) ecological tension. The values of basic integral indices of the landscape-ecological analysis were calculated as sums of respective factors expressed in scores and multiplied by their significance reflecting coefficients. In agreement with that rule, a formula was derived of calculation of basic indices of landscape-ecological analysis. Subsequently, those factors were integrated by ‘Model Builder’ in ArcGIS applying ‘Weighted Sum’ functions. Finally, through geographic information systems modelling, maps of basic indices of landscape-ecological analysis were produced. In conclusion – ecological potential, stability, load and tension are best indicators for the assessment of the landscape-ecological situation of the studied territory.     

Separation of global time-variable gravity signals into maximally independent components

The Gravity Recovery and Climate Experiment (GRACE) products provide valuable information about total water storage variations over the whole globe. Since GRACE detects mass variations integrated over vertical columns, it is desirable to separate its total water storage anomalies into their original sources. Among the statistical approaches, the principal component analysis (PCA) method and its extensions have been frequently proposed to decompose the GRACE products into space and time components. However, these methods only search for decorrelated components that on the one hand are not always interpretable and on the other hand often contain a superposition of independent source signals. In contrast, independent component analysis (ICA) represents a technique that separates components based on assumed statistical independence using higher-order statistical information. If one assumes that independent physical processes generate statistically independent signal components added up in the GRACE observations, separating them by ICA is a reliable strategy to identify these processes. In this paper, the performance of the conventional PCA, its rotated extension and ICA are investigated when applied to the GRACE-derived total water storage variations. These analyses have been tested on both a synthetic example and on the real GRACE level-2 monthly solutions derived from GeoForschungsZentrum Potsdam (GFZ RL04) and Bonn University (ITG2010). Within the synthetic example, we can show how imposing statistical independence in the framework of ICA improves the extraction of the ‘original’ signals from a GRACE-type super-position. We are therefore confident that also for the real case the ICA algorithm, without making prior assumptions about the long-term behaviour or on the frequencies contained in the signal, improves over the performance of PCA and its rotated extension in the separation of periodical and long-term components.