Opportunities for satellite remote sensing in hydrology and water management

Abstract

Hydrology and Water Management are key areas of applied science in the current world economy. Increasingly hydrologiste are looking to satellite remote sensing to help meet their needs for near real‐time data to measure, monitor and model water in the environment. However, progress has been hindered by the lack of a dedicated series of hydro‐logical satellites.

The paper summarises studies undertaken on an international basis in order to influence satellite, sensor and ground segment design operations to suit the needs of water management.     

Earth observations during space shuttle flight STS‐41: Discovery's mission to planet earth

Abstract

Multi‐temporal ERS‐1 SAR data acquired over a large agricultural region in West Bengal was used to classify kharif crops like rice, jute and sugarcane. Rice crop grown under lowland management practice showed a temporal characteristic. The dynamic range of backscatter was highest for this crop in temporal SAR data. This was used to classify rice using temporal SAR data. Such temporal character was not observed for the other study crops, which may be due to the difference in cultivation practice and crop calendar. Significant increase in backscatter from the ploughed fields was used to derive information on onset and duration of land preparations. Synergistic use of optical remote sensing data and SAR data increased the separability of rice crop from homesteads and permanent vegetation classes.     

Modeling sprawl of unauthorized development using geospatial technology: case study in Kuantan district,Malaysia

Abstract

The paper explores a framework combining remote sensing and GIS-cellular automata (CA) concepts aimed at improving the modeling of unauthorized land use sprawl. Remote sensing data have been used in urban modeling and analysis, the use of high-resolution remote sensing data in assessing unauthorized development is quite unexplored. This work has demonstrated systematic combination utilization of geospatial analyses tools to acquire a new level of information to enable urban modeling and sprawl analysis in assisting urban sustainable management. In this study, Kuantan city, Malaysia was selected in simulation of the unauthorized land use with CA concept for a period of 15 years (2000–2015), with main input time-series land use observation from 1995 to 2005. The 2000 and 2005 land use input was also used as calibrated and test assessment of the simulation. The results show excellent agreement between in-situ changes of the unauthorized land use classes and the corresponding simulated classes within the same periods. In conclusion, CA model can lead to new levels of understanding of how urban areas grow and change as in view of digital earth aspiration.     

Remote sensing heritage in a petabyte-scale: satellite data and heritage Earth Engine© applications

ABSTRACT

This paper aims to demonstrate results and considerations regarding the use of remote sensing big data for archaeological and Cultural Heritage management large scale applications. For this purpose, the Earth Engine© developed by Google© was exploited. Earth Engine© provides a robust and expandable cloud platform where several freely distributed remote sensing big data, such as Landsat, can be accessed, analysed and visualized. Two different applications are presented here as follows: the first one is based on the evaluation of multi-temporal Landsat series datasets for the detection of buried Neolithic tells (‘magoules’) in the area of Thessaly, in Greece using linear orthogonal equations. The second case exploits European scale multi-temporal DMSP-OLS Night-time Lights Time Series to visualize the impact of urban sprawl in the vicinity of UNESCO World Heritage sites and monuments. Both applications highlight the considerable opportunities that big data can offer to the fields of archaeology and Cultural Heritage, while the studies also demonstrate the great challenges that still are needed to be overcome in order to make the exploitation of big data process manageable and fruitful for future applications.     

Earth observations during space shuttle mission STS‐45 mission to planet earth March 24—April 2, 1992

Abstract

The impact of animals upon the landscape, through such actions as trampling, feeding, burrowing, mounding, and dam building, is a topic of interest in university geography classrooms. However, the relatively fine‐scale nature of most such impacts precludes its examination via remote sensing. Nevertheless, remote sensing of many types of animal impact is possible, and in this paper I illustrate several such examples, primarily drawn from free‐access sites on the World Wide Web, using a variety of remote sensing platforms. Instructors of physical geography or resource/land use management courses can thus introduce a variety of remote sensing concepts and imagery types in their classrooms while at the same time examining the role of animals on the landscape.     

Large-scale urban functional zone mapping by integrating remote sensing images and open social data

ABSTRACT

Urban functional zones (UFZs) are important for urban sustainability and urban planning and management, but UFZ maps are rarely available and up-to-date in developing countries due to frequent economic and human activities and rapid changes in UFZs. Current methods have focused on mapping UFZs in a small area with either remote sensing images or open social data, but large-scale UFZ mapping integrating these two types of data is still not be applied. In this study, a novel approach to mapping large-scale UFZs by integrating remote sensing images (RSIs) and open social data is proposed. First, a context-enabled image segmentation method is improved to generate UFZ units by incorporating road vectors. Second, the segmented UFZs are classified by coupling Latent Dirichlet Allocation (LDA) and Support Vector Machine (SVM). In the classification framework, physical features from RSIs and social attributes from POI (Point of Interest) data are integrated. A case study of Beijing was performed to evaluate the proposed method, and an overall accuracy of 85.9% was achieved. The experimental results demonstrate that the presented method can provide fine-grained UFZs, and the fusion strategy of RSIs and POI data can distinguish urban functions accurately. The proposed method appears to be promising and practical for large-scale UFZ mapping.     

Web service for biodiversity estimation using remote sensing data

Abstract

This paper presents a technique for the assessment and mapping of land biodiversity by using remote sensing data. The proposed approach uses a fuzzy model that encapsulates different ecological factors influencing biodiversity. We implemented our approach as a web service for the Pre-Black Sea region of the Ukraine.     

Enhancing the OGC WPS interface with GeoPipes support for real-time geoprocessing

ABSTRACT

Real-time geospatial information is used in various applications such as risk management or alerting services. Especially, the rise of new sensing technologies also increases the demand for processing the data in real time. Today’s spatial data infrastructures, however, do not meet the requirements for real-time geoprocessing. The OpenGIS^® Web Processing Service (WPS) is not designed to process real-time workflows. It has some major drawbacks in asynchronous processing and cannot handle (geo) data streams out of the box. In previous papers, we introduced the GeoPipes approach to share spatiotemporal data in real time. We implemented the concept extending the Message Queue and Telemetry Transport (MQTT) protocol by a spatial and temporal dimension, which we call GeoMQTT. In this paper, we demonstrate the integration of the GeoPipes idea in the WPS interface to expose standardized real-time geoprocessing services. The proof of the concept is illustrated in some exemplary real-time geo processes.     

Parallelizing maximum likelihood classification on computer cluster and graphics processing unit for supervised image classification

ABSTRACT

Supervised image classification has been widely utilized in a variety of remote sensing applications. When large volume of satellite imagery data and aerial photos are increasingly available, high-performance image processing solutions are required to handle large scale of data. This paper introduces how maximum likelihood classification approach is parallelized for implementation on a computer cluster and a graphics processing unit to achieve high performance when processing big imagery data. The solution is scalable and satisfies the need of change detection, object identification, and exploratory analysis on large-scale high-resolution imagery data in remote sensing applications.     

Integrating spectral and non-spectral data to improve urban settlement mapping in a large Latin-American city

ABSTRACT

Information on urban settlements is crucial for sustainability planning and management. While remote sensing has been used to derive such information, its applicability can be compromised due to the complexity in the urban environment. In this study, we developed a remote sensing method to map land cover types in a large Latin-American city, which is well known for its mushrooming unplanned and informal settlements. After carefully considering the landscape complexity there, we designed a data fusion method combining multispectral imagery and non-spectral data for urban and land mapping. Specifically, we acquired a cloud-free Landsat-8 image and two non-spectral datasets, i.e., digital elevation models and road networks. Then, we implemented a set of experiments with different inputs to evaluate their merits in thematic mapping through a supervised protocol. We found that the map generated with the multispectral data alone had an overall accuracy of 73.3% but combining multispectral imagery and non-spectral data yielded a land cover map with 90.7% overall accuracy. Interestingly, the thermal infrared information helped substantially improve both the overall and categorical accuracies, particularly for the two urban classes. The two types of non-spectral data were critical in resolving several spectrally confused categories, thus considerably increasing the mapping accuracy. However, the panchromatic band with higher spatial resolution and its derived textural measurement only generated a marginal accuracy improvement. The novelties of our work are with the successful separation between the two major types of urban settlements in a complex environment using a carefully designed data fusion approach and the insight into the relative merits of the thermal infrared information and non-spectral data in helping resolve the issue of class ambiguity. These findings should be valuable in deriving accurate urban settlement information which can further advance the research on socio-ecological dynamics and urban sustainability.     

Integrated GIS and Remote Sensing Approach to Map Pollution in Upper Lake,Bhopal, India

Abstract

Upper Lake is the lifeline of Bhopal City, India for drinking and other water needs. In recent years, environmentalists have expressed their serious concern on deteriorating water quality of this lake. Conventional field sampling methods for monitoring lake water quality lack spatial information about the pollution in the lake. It is desirable to have spatial information about the lake for better management and control. In the present paper the remote sensing data from IRS-1C LISS III have been integrated into a GIS environment to analyse and create a pollution zone map of the Upper Lake.

Spectral reflectance analysis was carried out to find the suitability of wavelengths for determining chlorophyll‐a concentration (chl‐a), suspended solid concentration (SSC) and secchi depth (SD). Empirical models relating spectral reflectance and chl‐a, SSC and SD were developed using least square regression analysis. These models were found valid on unused samples. Chl‐a, SSC and SD distribution maps were generated using proposed models and were incorporated as datalayers in the GIS for further analysis of pollution zones. The spatial information of pollution offered by the pollution zone map could delineate regions of lake having high pollution load. The methodology employed in this work can be used for regular monitoring of the pollution in surface water bodies and serve the data needs for better management of the water quality.     

Delineating a Study Area Within a Rectangular Data Set: A Class Exercise

Abstract

This article deals with an image processing exercise used in a university undergraduate remote sensing course. The exercise shows students some techniques for delineating a non‐rectangular study area within a rectangular image data set. Rectangular data sets frequently create problems for students when their areas of interest arepolygonal in shape. An inexpensive image processing software package called Earthscope is used in this exercise.     

The SPOT satellites: From SPOT 1 to SPOT 4

Abstract

The recently launched SPOT 1 satellite belongs to a family of second generation remote sensing spacecraft which has been designed to ensure more than 10 years of continuity for the corresponding data delivery.

Starting with the model 1 of the satellite series, the paper describes successively its sun synchronous orbit, the 2 identical imaging instruments and the other subsystems such as the on board tape recorders, the telemetry package, the stabilization equipments and etc. Special emphasis is given to the technological innovations put into the design of this satellite, and its twin model 2, with respect to the first generation satellites represented by the three first spacecraft of LANDSAT Series.

The paper then details the improvements carried out on the design of the 3rd and 4th models, to ensure the service continuity beyond 1990, and to deliver even more powerful data in terms of potential applications.     

Mapping leafy spurge (euphorbia esula) infestations using aerial photography and geographic information systems

Abstract

Leafy spurge is a troublesome weed on the northern Great Plains of the United States that chemicals and grazing management have not controlled. Remote sensing and geographic information system (GIS) technology have been used to detect and monitor numerous grassland related problems. The objectives of this study were to use both technologies to map and quantify the extent of leafy spurge within Theodore Roosevelt National Park and to provide information for managing the infestation. Analysis of the data indicated that 702 ha of the 18,680 ha park were infested by leafy spurge; however, leafy spurge populations occurring under dense woody canopies, in deep stream channels, and on steep slopes were not always detected. Infestations were especially dense in the western and southeast portions of the park. Most infestations were restricted to riparian zones and smaller drainage channels. Leafy spurge infestations decreased exponentially as distance from stream channels increased (r²=0.98). The significant association of leafy spurge with drainage channels suggests that the weed might be effectively managed on a watershed sub‐basin level. The joint use of GIS and remote sensing proved to be a powerful combination of tools which provided previously unavailable information about the extent and spatial dynamics of leafy spurge within the park. The results of this study will contribute to the development of a comprehensive leafy spurge management plan for Theodore Roosevelt National Park (South Unit).     

Developing spatially and thematically detailed backdated maps for land cover studies

ABSTRACT

Global or regional land cover change on a decadal time scale can be studied at a high level of detail using the availability of remote sensing data such as that provided by Landsat. However, there are three main technical challenges in this goal. First, the generation of land cover maps without reference data is problematic (backdating). Second, it is important to maintain high accuracies in land cover change map products, requiring a reasonably rich legend within each map. Third, a high level of automation is necessary to aid the management of large volumes of data. This paper describes a robust methodology for processing time series of satellite data over large spatial areas. The methodology includes a retrospective analysis used for the generation of training and test data for historical periods lacking reference information. This methodology was developed in the context of research on global change in the Iberian Peninsula. In this study we selected two scenes covering geographic regions that are representative of the Iberian Peninsula. For each scene, we present the results of two classifications (1985–1989 and 2000–2004 quinquennia), each with a legend of 13 categories. An overall accuracy of over 92% was obtained for all 4 maps.     

The Potential of Virtual Reality Technology for Analysis of Remotely Sensed Data: A Lidar Case Study

Abstract

Although the GIS community has been quick to exploit the advantages of virtual reality (VR) for display and analysis of spatial data, VR does not appear to have been exploited widely for remote sensing data analysis. A case study of high resolution lidar data acquired over a deciduous forest near Morgantown, WV was used to investigate the potential and limitations of current VR software for remote sensing analysis. The functionality within a standard remote sensing software package was found to provide a good overview of interpolated, smoothed lidar data, but was less useful for gridded data that had not been interpolated. With gridded data, it was possible to drape orthophotographs or other images over the lidar data, providing a useful method for investigating relationships between lidar and other data. Alternatively, using a commercial VR package, it was possible to view the original lidar point data, and thus visualize the multiple returns from within the canopy of each tree. The point data were preferable for identification of surfaces within the data cloud, especially the ground surface. For a fully integrated remote sensing VR package, functionality will be needed to link point and interpolated coverages, and also to enhance the interactive selection of data for further statistical analysis.     

Procedures for woody vegetation surveys in the Kazgail rural council area,Kordofan, Sudan

Efforts to reforest parts of the Kordofan Province of Sudan are receiving support from international development agencies. These efforts include planning and implementing reforestation activities that require the collection of natural resources and socioeconomic data, and the preparation of base maps. A combination of remote sensing, geographic information system and global positioning systems procedures are used in this study to meet these requirements.

Remote sensing techniques were used to provide base maps and to guide the compilation of vegetation resources maps. These techniques provided a rapid and efficient method for documenting available resources. Pocket‐sized global positioning system units were used to establish the location of field data collected for mapping and resource analysis. A microcomputer data management system tabulated and displayed the field data. The resulting system for data analysis, management, and planning has been adopted for the mapping and inventory of the Gum Belt of Sudan.     

Mapping alteration mineral zones and lithological units in Antarctic regions using spectral bands of ASTER remote sensing data

Abstract

Geological mapping is one of the primary tasks of remote sensing. Remote sensing applications are especially useful when extreme environmental conditions inhibit direct survey such as in Antarctica. In this investigation, a satellite-based remote sensing approach was used for mapping alteration mineral zones and lithological units using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data in the Oscar II coast area, north-eastern Graham Land, Antarctic Peninsula. Specialized band ratios and band combinations were developed using visible and near infrared, shortwave infrared (SWIR) and thermal infrared spectral bands of ASTER for detecting alteration mineral assemblages and lithological units in Antarctic environments. Constrained Energy Minimization, Orthogonal Subspace Projection and Adaptive Coherence Estimator algorithms were tested to ASTER SWIR bands for detecting sub-pixels’ abundance of spectral features related to muscovite, kaolinite, illite, montmorillonite, epidote, chlorite and biotite. Results indicate valuable applicability of ASTER data for Antarctic geological mapping.     

The Sensor Web: systems of sensor systems

Abstract

Global Earth Observing System of Systems (GEOSS) presents a great challenge of System of Systems integration across organisational and political boundaries. One existing paradigm that can address the scale of the challenge is that of the Sensor Web. In this paradigm, the internet is evolving into an active, macro sensing instrument, capable of drawing sensory data from around the globe to the fingertips of individuals. The Sensor Web will support scientific research and facilitate transparent political decision making. This article presents some of the technologies explored and activities engaged in by the GEOSS Sensor Web community, towards achieving GEOSS goals.