An Integration of Spatial Information Technology for Groundwater Potential and Quality Investigations in Koduvan Ár Sub-Watershed of Meenachil River Basin,Kerala, India

The importance of groundwater is growing based on an increase in need and decrease in the availability of fresh surface water sources and adequate rainfall. Remote Sensing and Geographic Information System (GIS) has become one of the leading tools in the field of hydrogeological science, which helps in assessing, monitoring and conserving groundwater resources. This paper describes the results of a groundwater potentiality and quality assessment conducted in Koduvan ár sub-watershed of Meenachil river basin, Kottayam district of Kerala state, in the Republic of India. Shallow groundwater is the main source of drinking water in urban and rural areas, but reliable spatial data on its potentiality and quality are currently insufficient for developing the water-supply systems with standard designs. The methodology used in the present study includes an integrated approach of remote sensing and GIS for the construction of groundwater potentiality map and the assessment of water quality of identified wells. Different spatial data layers such as, geomorphology, lithology, slope and land use/ land cover are generated and the interrelationship between these layers were analyzed to identify and assess the groundwater potentiality of the area. The final result depicts the favourable prospective zones in the study area with its quality parameters and can be helpful to formulate recommendations to reduce the water scarcity and quality risks for public health.     

Application of DEM,Remote Sensing and Geomorphic Studies in Identifying a Recent [or perhaps Neogene?] Upwarp in the Dibru River Basin,Assam, India

The Dibru river basin of Assam is investigated to examine the influence of active structure by applying an integrated study on geomorphology, morphotectonics, subsurface structure, Digital Elevation Model (DEM) using topographic map, IRS 1D LISS III, IRS P6 LISS III, SRTM, seismic and subsurface data. Seismic data reveals existence of an upwarp and an important fault in the basement around the central and eastern parts of the Dibru basin, respectively. The influence of these structures is well observed on all the younger formations inferring their active nature possibly till the Recent Period. Existence of fluvial anomalies, viz. annular drainage pattern, lineaments, abrupt changes in the direction of river course, beheaded stream and valley incision infer role of structural control on the fluvial features of this basin. Most commonly used indices for morphotectonic analysis, viz. basin elongation ratio (Re), transverse topographic symmetry (T), asymmetric factor (AF), valley floor width to valley height ratio (Vf) have been used to identify the evidences of active structures in the area. The values of Re indicated tectonically active, T indicated an asymmetric nature, AF indicated tilting and Vf indicated active incision in the Dibru basin. The DEM, profiles across the valley and superimposed longitudinal profiles of incised channel bed and valley shoulder of the Dibru clearly reveal valley incision by the river. Three large paleochannels located in different parts of the basin had their headwaters towards east at the common source, i.e. the Diyun river. These paleochannels had been resulted when their headwaters avulsed to create new rivers due to affect of the subsurface structures during Recent (or perhaps Neogene?) Period.     

GIS-based ordered weighted averaging and Dempster–Shafer methods for landslide susceptibility mapping in the Urmia Lake Basin,Iran

In this paper, GIS-based ordered weighted averaging (OWA) is applied to landslide susceptibility mapping (LSM) for the Urmia Lake Basin in northwest Iran. Nine landslide causal factors were used, whereby the respective parameters were extracted from an associated spatial database. These factors were evaluated, and then the respective factor weight and class weight were assigned to each of the associated factors using analytic hierarchy process (AHP). A landslide susceptibility map was produced based on OWA multicriteria decision analysis. In order to validate the result, the outcome of the OWA method was qualitatively evaluated based on an existing inventory of known landslides. Correspondingly, an uncertainty analysis was carried out using the Dempster–Shafer theory. Based on the results, very strong support was determined for the high susceptibility category of the landslide susceptibility map, while strong support was received for the areas with moderate susceptibility. In this paper, we discuss in which respect these results are useful for an improved understanding of the effectiveness of OWA in LSM, and how the landslide prediction map can be used for spatial planning tasks and for the mitigation of future hazards in the study area.     

Hydrological and hydrodynamic modeling for flood damage mitigation in Brahmani–Baitarani River Basin,India

Stream flow forecast and its inundation simulations prior to the event are an effective and non-structural method of flood damage mitigation. In this paper, a continuous simulation hydrological and hydrodynamic model was developed for stream flow forecast and for spatial inundation simulation in Brahmani–Baitarani river basin, India. The hydrologic modelling approach includes rainfall-run-off modelling, flow routing, calibration and validation of the model with the field discharge data. CARTOSAT Digital Elevation Model of 30 m resolution, land use/land cover derived from the Indian Remote Sensing Satellite (IRS-P6) AWiFS and soil textural data of the study area were used in the modelling to compute topographic and hydraulic parameters. The hydrological model was calibrated with the help of field observed discharge data of 2006 and 2009 and validated with the data of 2008 and 2011. From the results, it is found that computed discharges are very well matching well with the observed discharges. The developed model can provide the stream flow forecast with more than 30 h lead time. Possible flood inundations were simulated using hydrodynamic modelling approach. CARTO Digital Elevation Model of 10 m resolution, landuse and the computed flood hydrographs were used in inundation simulations.     

Mapping and Assessment of Groundwater Potential in Bilrai Watershed (Shivpuri District, M.P.)—A Geomatics Approach

The main objective of the present work is to delineate the groundwater potential zones in Bilari watershed of district Shivpuri, Madhya Pradesh. Remote Sensing data and GIS were used to delineate the groundwater potential zones of the area. IRS-1D (LISS III) data have been utilized to extract information on various themes such as geomorphology, structure, drainage and land use/land cover. Available lithology and soil maps have also been used. DEM has been generated from contours taken from Survey of India topographical maps in order to obtain the slope percentage and slope aspect of the area. The groundwater potential zones were delineated by weighted overlay analysis. The themes geology, geomorphology, slope and soil were considered and the weightages assigned to different classes of respective themes according to their role in groundwater potential. Finally, five groundwater potential zones viz., very good, good, moderate; poor and very poor were delineated for the study area. It was estimated that about 110.41?sq km area which forms 37.55% of the total area are in the zones of very poor, poor and moderate category and about 183.75?sq km (62.45%) in zones of good and very good category.     

A COM-based Framework for Management, Analysis and Visualization of Large Scope Digital Elevation Models

This paper presents a component object model (COM) based framework for managing, analyzing and visualizing massive multi-scale digital elevation models (DEMs). The framework consists of a data manage-ment component (DMC), which is based on RDBMS/ORDBMS, a data a-nalysis component (DAC) and a data render component (DRC). DMC can manage massive multi-scale data ex-pressed at various reference frames within a pyramid database and can support fast access to data at variable resolution. DAC integrates many use-ful applied analytic functions whose re-sults can be overlaid with the 3D scene rendered by DRC. DRC provides view-dependent data paging with the sup-port of the underlying DMC and or-ganizes the potential visible data at dif-ferent levels into rendering.     

Spatially variable surface elevation changes and estimated melt water contribution of Continental Glacier in the Wind River Range,Wyoming, USA: 1966–2011

Seasonal snow melt in the Wind River Range, Wyoming, has been ending earlier over the last several decades leaving the region to rely more on supplemental melt water from mountain glaciers. This leads to the necessity of understanding recent glacial changes. This study uses elevation data from 1966, 2006 and 2011 to calculate surface elevation and volume changes that have occurred on Continental Glacier. Results indicate a mean volume change of ?0.034 ± 0.02 km³ and surface elevation change of ?0.36 ± 0.19 m y^?1 between 1966 and 2006. Detailed spatial analysis shows that the glacier is divided into two sections which are thinning at different rates (lower section: ?0.06±0.19 m y^?1; upper section: ?0.51 ± 0.19 m y^?1). The upper section has experienced 97% of the thinning (or 742.5 × 10³ m³ of melt water equivalent per year) and increased its rate since 2006 by 27.5%.     

Application of Remote Sensing and GIS Technology to the Study of Desertification of Arable Lands in North Shaanxi, China

The policy of the Chinese government concerning the horizontal expansion of the cultivated land through the reclamation of desert soils result in a total increase of 665. 985 km^2 during the period 1987-1999 in North Shaanxi. This increase is less than the loss in arable land by urbanization. The accelerated rate of change in agricultural areas calls for more rapid surveys of urbanization and loss of arable land. Remote sensing has a number of advantages over ground-based methods for such surveys. The multi-scale concept of remote sensing data help us study the problem in four towns. Several maps were produced to analyze the situation of urban coverage in different times. The evaluation of the status, rate and risk of urbanization are based on an accepted average of urban increase as 2% of population growth per year.     

Dynamics of inequality and growth in Europe: may spatial models solve the puzzle?

Journal of Geographical Systems - The link between income inequality and economic growth remains poorly understood. The global economic crisis challenged numerous growth studies by highlighting...     

Land use and land cover changes over a century (1914–2007) in the Neyyar River Basin,Kerala: a remote sensing and GIS approach

Abstract

Land use and land cover change, perhaps the most significant anthropogenic disturbance to the environment, mainly due to rapid urbanization/industrialization and large scale agricultural activities. In this paper, an attempt has been made to appraise land use/land cover changes over a century (1914–2007) in the Neyyar River Basin (L=56 km; Area = 483.4 km²) in southern Kerala – a biodiversity hot spot in Peninsular India. In this study, digital remote sensing data of the Indian Remote Sensing satellite series I-D (LISS III, 2006–2007) on 1:50,000 scale, Survey of India (SOI) toposheet of 1914 (1:63,360) and 1967 (1:50,000) have been utilized to map various land use/land cover changes. Maps of different periods have been registered and resampled to similar geographic coordinates using ERDAS Imagine 9.0. The most notable changes include decreases in areas of paddy cultivation, mixed crops, scrub lands and evergreen forests, and increases in built-up areas, rubber plantations, dense mixed forests, and water bodies. Further, large scale exploitation of flood plain mud and river sand have reached menacing proportions leading to bank caving and cut offs at channel bends. Conservation of land and water resources forms an important aspect of ecosystem management in the basin.     

Feasibility of estimating heavy metal contaminations in floodplain soils using laboratory-based hyperspectral data—A case study along Le’an River,China

It is necessary to estimate heavy metal concentrations within soils for understanding heavy metal contaminations and for keeping the sustainable developments of ecosystems. This study, with the floodplain along Le’an River and its two branches in Jiangxi Province of China as a case study, aimed to explore the feasibility of estimating concentrations of heavy metal lead (Pb), copper (Cu) and zinc (Zn) within soils using laboratory-based hyperspectral data. Thirty soil samples were collected, and their hyperspectral data, soil organic matters and Pb, Cu and Zn concentrations were measured in the laboratory. The potential relations among hyperspectral data, soil organic matter and Pb, Cu and Zn concentrations were explored and further used to estimate Pb, Cu and Zn concentrations from hyperspectral data with soil organic matter as a bridge. The results showed that the ratio of the first-order derivatives of spectral absorbance at wavelengths 624 and 564 nm could explain 52% of the variation of soil organic matter; the soil organic matter could explain 59%, 51% and 50% of the variation of Pb, Cu and Zn concentrations with estimated standard errors of 1.41, 48.27 and 45.15 mg·kg?; and the absolute estimation errors were 8%–56%, 12%–118% and 2%–22%, and 50%, 67% and 100% of them were less than 25% for Pb, Cu and Zn concentration estimations. We concluded that the laboratory-based hyperspectral data hold potentials in estimating concentrations of heavy metal Pb, Cu and Zn in soils. More sampling points or other potential linear and non-linear regression methods should be used for improving the stabilities and accuracies of the estimation models.     

Monitoring of deforestation and land use changes (1925–2012) in Idukki district,Kerala, India using remote sensing and GIS

The studies on forest cover change can reveal the status of forests and facilitate for its conservation planning. Idukki is the largest district in the state of Kerala having a total geographical area of 5019 km². The objectives of the present study are to map forest cover in Idukki district using multi-temporal remote sensing data (1975, 1990, 2001 and 2012) and topographical maps (1925), to analyze the trends in deforestation and land use changes. Overall statistics for the period of 1925 indicate that about 4675.7 km² (93.2 %) of the landscape was under forest. The forest cover in 2012 was estimated as 2613.4 km² (52.1 %). Recently, due to the implementation of policies and protection efforts, the rate of deforestation was greatly reduced. The commencement of hydroelectric projects during 1925–1990 responsible for an increase of area under water bodies by inundating other land uses. The long term analysis shows agricultural area been decreasing and commercial plantations been increasing in the district. There has been a significant increase in the area of plantations from 1236.2 km² (1975) to 1317.3 km² (2012).     

Feasibility of Estimating Heavy Metal Contaminations in Floodplain Soils Using Laboratory-Based Hyperspectral Data—A Case Study Along Le’an River, China

It is necessary to estimate heavy metal concentrations within soils for understanding heavy metal contaminations and for keeping the sustainable developments of ecosystems.This study,with the floodplain along Le’an River and its two branches in Jiangxi Province of China as a case study,aimed to explore the feasibility of estimating concentrations of heavy metal lead(Pb),copper(Cu) and zinc(Zn) within soils using laboratory-based hyperspectral data.Thirty soil samples were collected,and their hyperspectral data,soil organic matters and Pb,Cu and Zn concentrations were measured in the laboratory.The potential relations among hyperspectral data,soil organic matter and Pb,Cu and Zn concentrations were explored and further used to estimate Pb,Cu and Zn concentrations from hyperspectral data with soil organic matter as a bridge.The results showed that the ratio of the first-order derivatives of spectral absorbance at wavelengths 624 and 564 nm could explain 52% of the variation of soil organic matter;the soil organic matter could ex-plain 59%,51% and 50% of the variation of Pb,Cu and Zn concentrations with estimated standard errors of 1.41,48.27 and 45.15 mg·kg-1;and the absolute estimation errors were 8%-56%,12%-118% and 2%-22%,and 50%,67% and 100% of them were less than 25% for Pb,Cu and Zn concentration estimations.We concluded that the laboratory-based hyperspectral data hold potentials in esti-mating concentrations of heavy metal Pb,Cu and Zn in soils.More sampling points or other potential linear and non-linear regression methods should be used for improving the stabilities and accuracies of the estimation models.     

What path and how fast? The effect of flight time and path on user spatial understanding in map tour animations

GIScience scholars have identified map tours as an important visualization type for communicating spatial information: map tours are animations where the virtual camera moves through space and are common on the web, mobile devices, and television. Understanding how to enhance their effectiveness is timely because of recent, growing interest in virtual reality and animated map presentation tools such as Esri Story Maps? and Google Earth? tours. Despite this popularity, little empirical evidence exists about how people learn from map tours and how they should best be designed to improve effectiveness. This research is aimed at answering that need. An empirical study is described, which was designed to understand how virtual camera speed, path, and dynamic tilting within a map tour influence subjects’ ability to develop survey knowledge. The results of the experiment show that paths encompassing overviews of the landscape improve the viewer’s ability to build up survey knowledge; that tilting appears to have a much weaker effect; and that combining fast speed and a difficult path within a map tour increases the viewer’s cognitive load.     

The dynamics in the distribution of mangrove forests in Pichavaram,South India – perception by user community and remote sensing

This study aims to monitor the forest cover of Pichavaram mangroves, South India over a period of 40 years using remote sensing, and to record the status of mangroves as perceived by the local community. Out of 1471 ha of total reserved forest area, mangroves occupy 906 ha. The remote sensing maps show that there was a loss of 471 ha from 1970 to 1991 and a gain of 531 ha in 2011. Nearby 20 hamlets depend on mangroves for their livelihood. A village survey conducted at Pichavaram shows that more than 90% of the local community is well aware of the prevailing species, their importance especially after the 2004 tsunami and the impact of management practices, increased rainfall and contribution of local community in the recent increased area of mangroves. The same can be noticed from the high-resolution IKONOS image showing the artificial canal network in the restored region and from rainfall records.     

Whither goes the “maps” course? Maintaining map-use concepts,skills, and appreciation in GIS&T curricula

Popular and professional interest in maps and map-making has never been greater. Despite this engagement, introductory skills courses in “map use” have largely disappeared in undergraduate geography and cartography programs at US universities, with research indicating that both map-use course enrollments and the existence of such courses themselves are on the decline. While the map-use course and its content may have been replaced by, repackaged as, or incorporated into an integrated geographical information systems-cartography–remote sensing foundations course, how do we ensure that an understanding of maps and their unique characteristics is not lost in the mix? This essay describes a recent course redesign experience incorporating information literacy, technology fluency, and spatial thinking principles to maintain map-use concepts, skills, and appreciation in an introductory geographic information science and technology (GIS&T) foundations course, meeting both GIS&T and general education curricular goals.     

Variations in annual snowline and area of an ice-covered stratovolcano in the Cordillera Ampato,Peru, using remote sensing data (1986–2014)

This research focuses on the recent variations in the annual snowline and the total glaciated area of the Nevado Coropuna in the Cordillera Ampato, Peru. Maximum snowline altitude towards the end of dry season is taken as a representative of the equilibrium line altitude of the year, which is an indirect measurement of the annual mass balance. We used Landsat and IRS LISS3 images during the last 30 years due to its better temporal coverage of the study site. It is found that there was a decrease of 26.92% of the glaciated area during 1986–2014. We calculated the anomalies in precipitation and temperature in this region and also tried to correlate the changes in glacier parameters with the combined influence of El Niño – Southern Oscillation (ENSO) and pacific decadal oscillation (PDO). It is concluded that the snowline of Nevado Coropuna has been fluctuated during ENSO, and maximum fluctuations were observed when ENSO and PDO were in phase.     

Identification of Landslide Scars in the Region of the Serra do Mar,São Paulo State,Brazil, Using Digital Image Processing and Spatial Analysis Tools

The objective of the present study, developed in a mountainous region in Brazil where many landslides occur, is to present a method for detecting landslide scars that couples image processing techniques with spatial analysis tools. An IKONOS image was initially segmented, and then classified through a Batthacharrya classifier, with an acceptance limit of 99%, resulting in 216 polygons identified with a spectral response similar to landslide scars. After making use of some spatial analysis tools that took into account a susceptibility map, a map of local drainage channels and highways, and the maximum expected size of scars in the study area, some features misinterpreted as scars were excluded. The 43 resulting features were then compared with visually interpreted landslide scars and field observations. The proposed method can be reproduced and enhanced by adding filtering criteria and was able to find new scars on the image, with a final error rate of 2.3%.     

How to compare movement? A review of physical movement similarity measures in geographic information science and beyond

In geographic information science, a plethora of different approaches and methods is used to assess the similarity of movement. Some of these approaches term two moving objects similar if they share akin paths. Others require objects to move at similar speed and yet others consider movement similar if it occurs at the same time. We believe that a structured and comprehensive classification of movement comparison measures is missing. We argue that such a classification not only depicts the status quo of qualitative and quantitative movement analysis, but also allows for identifying those aspects of movement for which similarity measures are scarce or entirely missing.

In this review paper we, first, decompose movement into its spatial, temporal, and spatiotemporal movement parameters. A movement parameter is a physical quantity of movement, such as speed, spatial path, or temporal duration. For each of these parameters we then review qualitative and quantitative methods of how to compare movement. Thus, we provide a systematic and comprehensive classification of different movement similarity measures used in geographic information science. This classification is a valuable first step toward a GIS toolbox comprising all relevant movement comparison methods.