Hyperspectral anomaly detection within the signal subspace

This letter describes the extension of signal subspace processing (SSP) to the arena of anomaly detection. In particular, we develop an SSP-based, local anomaly detector that exploits the rich information available in the multiple bands of a hyperspectral (HS) image. This SSP approach is based on signal processing considerations, and its entire formulation reduces to a straightforward (and intuitively pleasing) geometric and algebraic development. We extend the basic SSP concepts to the HS anomaly detection problem, develop an SSP HS anomaly detector, and evaluate this algorithm using multiple HS data files.     

Study on the urban heat island effects and its relationship with surface biophysical characteristics using MODIS imageries

This study assesses surface urban heat island (UHI) and its associated surface physical characteristics using remote sensing approaches. TERRA/MODIS images acquired in 2005 in three different seasons were selected to generate land surface tem-perature and surface characteristics for the Changsha-Zhuzhou-Xiangtan metropolitan area in China. The intensity of urban heat is-land effects and its seasonal variations were examined. The result showed that UHI effects were significant both in the summer and the spri...     

Integrating terrain and vegetation indices for identifying potential soil erosion risk area

The present paper offers an innovative method to monitor the change in soil erosion potential by integrating terrain and vegetation indices derived from remote sensing data. Three terrain indices namely, topographic wetness index (TWI), stream power index (SPI) and slope length factor (LS), were derived from the digital elevation model. Normalized vegetation index (NDVI) was derived for the year 1988 and 2004 using remote sensing images. K-mean clustering was performed on staked indices to categorize the study area into four soil erosion potential classes. The validation of derived erosion potential map using USLE model showed a good agreement. Results indicated that there was a significant change in the erosion potential of the watershed and a gradual shifting of lower erosion potential class to next higher erosion potential class over the study period.     

Use of service middleware based on ECHO with CSW for discovery and registry of MODIS data

Nowadays, NASA is producing several terabytes Moderate Resolution Imaging Spectroradiometer (MODIS) data everyday; how to find the data with criteria, such as specific times, locations, and scales using an international standard becomes more and more important. In this paper, a service-oriented architecture for use of the integration Earth Observation System Clearing-HOuse (ECHO) with the Open Geospatial Consortium (OGC) Catalogue Service—Web profile (CSW) is put forward. The architecture consists of three roles: a service requester (the user), a service provider (the ECHO metadata server), and a service broker (the GeoNetwork CSW and MODIS registry service middleware). The core component-MODIS registry service middleware includes three components: metadata fetcher, metadata transformer, and metadata register. The metadata fetcher is used to fetch metadata from ECHO metadata server; the metadata transformer is responsible for transform metadata from one form to another; the metadata register is in charge of registering ISO19139-based metadata to CSW. A prototype system is designed and implemented by using the service middleware technology and a standard interface and protocol. The feasibility and the response time of registry and retrieval of MODIS data are evaluated by means of a realistic LPDAAC_ECS MODIS data center. The implementation of this prototype system and the experiment show that the architecture and method is feasible and effective.     

Vulnerability Assessment and Earthquake Risk Mapping in Part of North Iran Using Geospatial Techniques

Earthquakes cause huge loss of lives and infrastructure every year in Iran. Many settlement areas (urban & rural) as well as Tehran, the capital city of Iran are located in the hazardous area. This research deals with the earthquake risk assessment and mapping based on recent remote sensing information on a GIS platform. The study area is part of Central Alborz in southern Caspian Sea and north of capital city of Tehran called Marzanabad area. It is a potentially high-risk zone as several earthquakes have occurred in the past. The study’s main objective is to develop an Earthquake Risk Map at the scale of 1:25,000 to identify high-risk zone and vulnerability areas to the settlements and infrastructure of area. Digital lineaments wear extraction and analysis for identification the faults using several RADAR and optical images with spatial analysis techniques. The probable faults were detected by superimposition of the lithological and geomorphologic features and their variance over the lineaments in a GIS environment. This research work involved fault identification on the remote sensed dataset as well as field studies and the risky areas were classified in the vicinity of the faults by applying different buffer with specifying distance of the source/site of risk to fault location. Statistical analysis of Earthquake Risk Map (ERM) by GIS indicated that 32% of the total area with about 66% of settlements and 52% of population is located in strongly high-risk and high-risk zone. Moderately low risk and low risk zones cover 38.67% of total area, which is free of settlements as well as population. The Earthquake map elaborated in this research work will be a useful tool for disaster management as well as urban and regional planning of future activities in the area.     

An Introduction to MODISI and SCMOD Methods for Correction of the MODIS Snow Assessment Algorithm

Detection, monitoring and precise assessment of the snow covered regions is an important issue. Snow cover area and consequently the amount of runoff generated from snowmelt have a significant effect on water supply management. To precisely detect and monitor the snow covered area we need satellite images with suitable spatial and temporal resolutions where we usually lose one for the other. In this study, products of two sensors MODIS and ASTER both on board of TERRA platform having low and high spatial resolution respectively were used. The objective of the study was to modify the snow products of MODIS by using simultaneous images of ASTER. For this, MODIS snow index image with high temporal resolution were compared with that of ASTER, using regression and correlation analysis. To improve NDSI index two methods were developed. The first method generated from direct comparison of ASTER averaged NDSI with those of MODIS (MODISI). The second method generated by dividing MODIS NDSI index into 10 codes according to their percentage of surface cover and then compared the results with the difference between ASTER averaged and MODIS snow indices (SCMOD). Both methods were tested against some 16 MODIS pixels. It is found that the precision of the MODISI method was more than 96%. This for SCMOD was about 98%. The RMSE of both methods were as good as 0.02.     

Accuracy improvement of ASTER stereo satellite generated DEM using texture filter

The grid DEM(digital elevation model) generation can be from any of a number of sources:for instance,analogue to digital conversion of contour maps followed by application of the TIN model,or direct elevation point modelling via digital photogrammetry applied to airborne images or satellite images.Currently,apart from the deployment of point-clouds from LiDAR data acquisition,the generally favoured approach refers to applications of digital photogrammetry.One of the most important steps in such deployment i...     

Geo-scape,a granularity depended spatialization tool for visualizing multidimensional data sets

Recently,the expertise accumulated in the field of geovisualization has found application in the visualization of abstract multidimensional data,on the basis of methods called spatialization methods.Spatialization methods aim at visualizing multidimensional data into low-dimensional representational spaces by making use of spatial metaphors and applying dimension reduction techniques.Spatial metaphors are able to provide a metaphoric framework for the visualization of information at different levels of gran...     

Late Cretaceous-Cenozoic history of the Lake Baikal depression and formation of its unique biodiversity

Independent methods of geological and molecular-biological chronologies have made it possible to define generally corresponding stages in the geological and biological evolution of the environments and communities of Lake Baikal since the Late Cretaceous, i.e., during the last 70 myr. All the abiotic elements drastically changed during geological evolution, with destruction of existing and formation of new natural complexes. Nevertheless, some specific zones retained relicts of former settings. The resulting present-day natural complex includes elements of different ages and geneses. Similar to different natural zones of the present-day Earth, which are populated by different biocoenoses, stages in the development of abiotic elements are also characterized by different faunal and floral assemblages. Some taxa were replaced by others, and the resulting aqueous biota of Lake Baikal includes different-age and ecologically different elements. The oldest groups of Baikal organisms appeared approximately 70 Ma ago, although the largest proportion of the lake biota started forming 4–3 Ma ago in response to the most drastic changes in the abiotic elements of the environment. The youngest taxa appeared 1.8 to 0.15 Ma ago, i.e., during the period when superdeep lake environments and mountainous glaciations were developing. The chronological coincidence of main stages in development of abiotic and biotic elements of the nature indicates their relationships. Particular transformations of abiotic elements and the probable mechanism of their influence on the evolution of living communities are also considered.     

Applying personal carbon trading: a proposed ‘Carbon,Health and Savings System’ for British Columbia,Canada

Addressing climate change requires the synergy of technological, behavioural and market mechanisms. This article proposes a policy framework that integrates the three, deploying personal carbon trading as a key element within a policy portfolio to reduce personal carbon footprints. It draws on policy and human motivation literatures that address the behavioural changes that may be needed in the context of a long-term threat such as climate change. This proposal builds on an analysis of the British Columbia carbon tax, international examples of carbon pricing instruments and strategies for behavioural change such as social networks, loyalty management, mobile apps and gamification. Interviews were conducted with experts in financial services, energy conservation and clean technology, as well as with specialists in climate, health and taxation policy. Their input, together with a review of the theoretical literature and practical case studies, informed the proposed design of a Carbon, Health and Saving System for promoting individual engagement and collective action by linking long-term climate mitigation measures with short-term personal and social goals, including health, recreation and social reinforcement.

Policy Relevance

This article identifies areas for climate policy innovation and recommends policies that can support, promote and enable personal carbon budgeting and collective action. Although this study is focused on British Columbia, both the input provided by key opinion leaders and the proposed framework are applicable to other jurisdictions.

This policy proposal shows how personal carbon trading could work in the context of a Canadian province with an existing climate mitigation policy. It also specifies a minimum viable product approach to establishing the economic, social and technological foundations for personal carbon trading.

The Carbon, Health and Saving System identifies the technologies and stakeholders needed to implement personal carbon trading, and offers the possibility of motivating a widespread conscious human response in the event that carbon taxation proves insufficient to generate economic adaptation in a changing climate.