Three‐dimensional displays for natural hazards analysis,using classified Landsat thematic mapper digital data and large‐scale digital elevation models

Abstract

Professional aerial photography missions are generally outside the reach of most students and faculty involved with teaching and research. Oblique aerial photography using handheld cameras for image acquisition from a light high‐wing aircraft offers an excellent learning experience for students in a first course in remote sensing and offers a useful research tool for graduate students and faculty engaged in environmental investigations. This paper is essentially a guide, covering all aspects of hand‐held camera aerial imaging and the subsequent processing needed to produce low‐obliques, stereograms, anaglyphs, and flight line mosaics. Scales, ground coverage distances, and stereogram and mosaic timing intervals, are included along with a section on the calculations used to produce these numbers. A list of additional resources concludes the paper.     

Mid‐infrared video: A possible tool for thermal analysis of wildfires

This paper demonstrates the applicability of a black‐and‐white visible‐infrared sensitive video camera, filtered to record radiation in the 1.45–2.0 μm mid‐infrared (MIR) spectral region, for detecting burning wood coals. Airbome imagery of a burned rangeland area and a wood fire at a dump site showed that hot spots (smoldering wood coals) could be delineated from other landscape features. MIR video imagery should be useful to detect burning wood coals at temperatures as low as 900K. These results indicate that the MIR video system may be a potential tool to aid wild‐land managers in the thermal analysis of wildfires.     

Enhanced change detection index for disaster response,recovery assessment and monitoring of buildings and critical facilities—A case study for Muzzaffarabad,Pakistan

The availability of Very High Resolution (VHR) optical sensors and a growing image archive that is frequently updated, allows the use of change detection in post-disaster recovery and monitoring for robust and rapid results. The proposed semi-automated GIS object-based method uses readily available pre-disaster GIS data and adds existing knowledge into the processing to enhance change detection. It also allows targeting specific types of changes pertaining to similar man-made objects such as buildings and critical facilities. The change detection method is based on pre/post normalized index, gradient of intensity, texture and edge similarity filters within the object and a set of training data. More emphasis is put on the building edges to capture the structural damage in quantifying change after disaster. Once the change is quantified, based on training data, the method can be used automatically to detect change in order to observe recovery over time in potentially large areas. Analysis over time can also contribute to obtaining a full picture of the recovery and development after disaster, thereby giving managers a better understanding of productive management and recovery practices. The recovery and monitoring can be analyzed using the index in zones extending from to epicentre of disaster or administrative boundaries over time.     

Mapping irrigated agriculture in complex landscapes using SPOT6 imagery and object-based image analysis – A case study in the Central Rift Valley,Ethiopia –

Irrigation infrastructure development for smallholder farmers in developing countries increasingly gains attention in the light of domestic food security and poverty alleviation. However, these complex landscapes with small cultivated plots pose a challenge with regard to mapping and monitoring irrigated agriculture. This study presents an object-based approach to map irrigated agriculture in an area in the Central Rift Valley in Ethiopia using SPOT6 imagery. The study is a proof-of-concept that the use of shape, texture, neighbour and location information next to spectral information is beneficial for the classification of irrigated agriculture. The underlying assumption is that the application of irrigation has a positive effect on crop growth throughout the field, following the field's borders, which is detectable in an object-based approach. The type of agricultural system was also mapped, distinguishing smallholder farming and modern large-scale agriculture. Irrigated agriculture was mapped with an overall accuracy of 94% and a kappa coefficient of 0.85. Producer's and user's accuracies were on average 90.6% and 84.2% respectively. The distinction between smallholder farming and large-scale agriculture was identified with an overall accuracy of 95% and a kappa coefficient of 0.88. The classifications were performed at the field level, since the segmentation was able to adequately delineate individual fields. The additional use of object features proved essential for the identification of cropland plots, irrigation period and type of agricultural system. This method is independent of expert knowledge on crop phenology and absolute spectral values. The proposed method is useful for the assessment of spatio-temporal dynamics of irrigated (smallholder) agriculture in complex landscapes and yields a basis for land and water managers on agricultural water use.     

A comparative predictive analysis of weighted overlay,weighted sum and fuzzy logic for mineral prospectivity mapping of precious and base metal mineralizations at north-east of Gümüşhane city,NE Turkey

The study area located south of the Eastern Pontide metallogenic belt (NE Turkey) has an important potential for valuable and base metallic minerals. Geological, tectonic, geochemical, hydrothermal alteration, mineralogical and fluid inclusion characteristics of ore formations in the region have been studied in detail. The purpose of this study is to combine and analyse the acquired spatial data layers in a geographic information system (GIS) environment using knowledge-driven approaches and to identify prospective areas in terms of mineralization. Moreover, evaluating the performance of different knowledge-driven mineral probability modelling results comparatively and quantitatively constitutes the other goal of the study. As a result, in addition to the known mineralization locations, a number of new prospective and favourable areas have been identified for future detailed studies. In addition, it has been found that the mineral predictive map generated using fuzzy logic-OR method produces the best and successful results compared to others.