Showing papers in "Geocarto International in 2016"

Flood susceptibility mapping using frequency ratio and weights-of-evidence models in the Golastan Province, Iran

Abstract: Flood is one of the most devastating natural disasters with socio-economic and environmental consequences. Thus, comprehensive flood management is essential to reduce the flood effects on human lives and livelihoods. The main goal of this study was to investigate the application of the frequency ratio (FR) and weights-of-evidence (WofE) models for flood susceptibility mapping in the Golestan Province, Iran. At first, a flood inventory map was prepared using Iranian Water Resources Department and extensive field surveys. In total, 144 flood locations were identified in the study area. Of these, 101 (70%) floods were randomly selected as training data and the remaining 43 (30%) cases were used for the validation purposes. In the next step, flood conditioning factors such as lithology, land-use, distance from rivers, soil texture, slope angle, slope aspect, plan curvature, topographic wetness index (TWI) and altitude were prepared from the spatial database. Subsequently, the receiver operating characteristic...

Rainfall-induced landslide susceptibility assessment at the Chongren area (China) using frequency ratio, certainty factor, and index of entropy

Abstract: The main objective of the study was to evaluate and compare the overall performance of three methods, frequency ratio (FR), certainty factor (CF) and index of entropy (IOE), for rainfall-induced landslide susceptibility mapping at the Chongren area (China) using geographic information system and remote sensing. First, a landslide inventory map for the study area was constructed from field surveys and interpretations of aerial photographs. Second, 15 landslide-related factors such as elevation, slope, aspect, plan curvature, profile curvature, stream power index, sediment transport index, topographic wetness index, distance to faults, distance to rivers, distance to roads, landuse, NDVI, lithology and rainfall were prepared for the landslide susceptibility modelling. Using these data, three landslide susceptibility models were constructed using FR, CF and IOE. Finally, these models were validated and compared using known landslide locations and the receiver operating characteristics curve. The resu...

Application of frequency ratio, weights of evidence and evidential belief function models in landslide susceptibility mapping

Abstract: The landslide hazard occurred in Taibai County has the characteristics of the typical landslides in mountain hinterland. The slopes mainly consist of residual sediments and locate along the highway. Most of them are in the less stable state and in high risk during rainfall in flood season especially. The main purpose of this paper is to produce landslide susceptibility maps for Taibai County (China). In the first stage, a landslide inventory map and the input layers of the landslide conditioning factors were prepared in the geographic information system supported by field investigations and remote sensing data. The landslides conditioning factors considered for the study area were slope angle, altitude, slope aspect, plan curvature, profile curvature, distance to faults, distance to rivers, distance to roads, normalized difference vegetation index, lithological unit, rainfall and land use. Subsequently, the thematic data layers of conditioning factors were integrated by frequency ratio (FR), weigh...

Delineation of groundwater potential zones using remote sensing and GIS-based data-driven models

Abstract: The rapid increase in human population has increased the groundwater resources demand for drinking, agricultural and industrial purposes. The main purpose of this study is to produce groundwater potential map (GPM) using weights-of-evidence (WOE) and evidential belief function (EBF) models based on geographic information system in the Azna Plain, Lorestan Province, Iran. A total number of 370 groundwater wells with discharge more than 10 m3s−1were considered and out of them, 256 (70%) were randomly selected for training purpose, while the remaining114 (30%) were used for validating the model. In next step, the effective factors on the groundwater potential such as altitude, slope aspect, slope angle, curvature, distance from rivers, drainage density, topographic wetness index, fault distance, fault density, lithology and land use were derived from the spatial geodatabases. Subsequently, the GPM was produced using WOE and EBF models. Finally, the validation of the GPMs was carried out using areas u...

Landscape transform and spatial metrics for mapping spatiotemporal land cover dynamics using Earth Observation data-sets

Abstract: Analysis of Earth observation (EO) data, often combined with geographical information systems (GIS), allows monitoring of land cover dynamics over different ecosystems, including protected or conservation sites. The aim of this study is to use contemporary technologies such as EO and GIS in synergy with fragmentation analysis, to quantify the changes in the landscape of the Rajaji National Park (RNP) during the period of 19 years (1990–2009). Several statistics such as principal component analysis (PCA) and spatial metrics are used to understand the results. PCA analysis has produced two principal components (PC) and explained 84.1% of the total variance, first component (PC1) accounted for the 57.8% of the total variance while the second component (PC2) has accounted for the 26.3% of the total variance calculated from the core area metrics, distance metrics and shape metrics. Our results suggested that notable changes happened in the RNP landscape, evidencing the requirement of taking appropriate...

Soil erosion prediction based on land cover dynamics at the Semenyih watershed in Malaysia using LTM and USLE models

Abstract: This study attempts to identify and forecast future land cover (LC) by using the Land Transformation Model (LTM), which considers pixel changes in the past and makes predictions using influential spatial features. LTM applies the Artificial Neural Networks algorithm) in conducting the analysis. In line with these objectives, two satellite images (Spot 5 acquired in 2004 and 2010) were classified using the Maximum Likelihood method for the change detection analysis. Consequently, LC maps from 2004 to 2010 with six classes (forest, agriculture, oil palm cultivations, open area, urban, and water bodies) were generated from the test area. A prediction was made on the actual soil erosion and the soil erosion rate using the Universal Soil Loss Equation (USLE) combined with remote sensing and GIS in the Semenyih watershed for 2004 and 2010 and projected to 2016. Actual and potential soil erosion maps from 2004 to 2010 and projected to 2016 were eventually generated. The results of the LC change detection...

A statistical significance of differences in classification accuracy of crop types using different classification algorithms

Abstract: Crop classification is needed to understand the physiological and climatic requirement of different crops. Kernel-based support vector machines, maximum likelihood and normalised difference vegetation index classification schemes are attempted to evaluate their performances towards crop classification. The linear imaging self-scanning (LISS-IV) multi-spectral sensor data was evaluated for the classification of crop types such as barley, wheat, lentil, mustard, pigeon pea, linseed, corn, pea, sugarcane and other crops and non-crop such as water, sand, built up, fallow land, sparse vegetation and dense vegetation. To determine the spectral separability among crop types, the M-statistic and Jeffries–Matusita (J–M) distance methods have been utilised. The results were statistically analysed and compared using Z-test and χ2-test. Statistical analysis showed that the accuracy results using SVMs with polynomial of degrees 5 and 6 were not significantly different and found better than the other classifica...

Assessment of a spatial multi-criteria evaluation to site selection underground dams in the Alborz Province, Iran

Abstract: Most part of Iran is arid and semi-arid; thus in most parts of the region, groundwater is the only source of water. This research presents a method based on a spatial multi-criterion evaluation (SMCE) for designing possible sites of underground dams and ranks them according to their suitability. The method was tested for siting underground dams in the Alborz Province, Iran. At first, screening algorithm was applied using exclusionary criteria, and thirty-one potential areas were recognized in the study area. In the next step, a suitable gorge or valley was recognized using the combination of basic maps and extensive field surveys (long axis of tank level) in each potential area. Subsequently, the analytical hierarchy process was used as a powerful tool for decision-making in the SMCE in order to evaluate different criteria for underground dam sites. SMCE techniques were then applied to combine the criteria, and obtain a suitability map in the study area. These sites were then compared and ranked according...

Assessment and validation of evapotranspiration using SEBAL algorithm and Lysimeter data of IARI agricultural farm, India

Abstract: Evapotranspiration (ET) is a vital process in land surface atmosphere research. In this study, Surface Energy Balance Algorithm for Land (SEBAL) for the assessment of ET (for 23 December 2010, 8 January 2011, 24 January 2011, 9 February 2011, 25 February 2011, 29 March 2011 and 14 April 2011) from LANDSAT7-ETM+ and validation with Lysimeter data set is illustrated. It is based on the evaporative fraction concept, and it has been applied to LANDSAT7-ETM + (30 m resolution) data acquired over the Indian Agricultural Research Institute’s agricultural farm land. The ET from SEBAL was compared with Lysimeter ET using four statistical tests (root-mean-square error (RMSE), relative root-mean-square error (R-RMSE), mean absolute error (MAE), and normalized root-mean square error (NRMSE)), and each test showed a good correlation between the predicted and observed ET values. Results from this study revealed that the RMSE of crop-growing period was 0.51 mm d−1 for ETSEBAL, i.e. ETSEBAL having good accuracy with resp...

An assessment of gully erosion along major armoured roads in south-eastern region of South Africa: a remote sensing and GIS approach

Abstract: An assessment of gully erosion along road drainage-release sites is critical for understanding the contribution of roads to soil loss and for informed land management practices. Considering that road-related gully erosion has traditionally been measured using field methods that are expensive, tedious and limited spatially as well as temporally, it is important to identify affordable, timely and robust methods that can be used to effectively map and estimate the volume of gullies along the road networks. In this study, gullies along major roads were identified from remotely sensed data sets and their volumes were estimated in a Geographic Information Systems environment. Also, the biophysical and climatic factors such as vegetation cover, the road contributing surface area, the gradient of the discharge hillslope and rainfall were derived from remotely sensed data sets using Geographic Information Systems techniques to find out whether they could explain the morphology of gullies that existed in this area....

Performance evaluation of land change simulation models using landscape metrics

Abstract: This study proposes a landscape metrics-based method for model performance evaluation of land change simulation models. To quantify model performance at both landscape and class levels, a set of composition- and configuration-based metrics including number of patches, class area, landscape shape index, mean patch area and mean Euclidean nearest neighbour distance were employed. These landscape metrics provided detailed information on simulation success of a cellular automata-Markov chain (CA-Markov) model standpoint of spatial arrangement of the simulated map versus the corresponding reference layer. As a measure of model simulation success, mean relative error (MRE) of the metrics was calculated. At both landscape and class levels, the MRE values were accounted for 22.73 and 10.2%, respectively, which are further categorised into qualitative measurements of model simulation performance for simple and quick comparison of the results. Findings of the present study depict a hierarchical and multi sp...

Utilization of high-resolution EGM2008 gravity data for geological exploration over the Singhbhum-Orissa Craton, India

Abstract: High-resolution EIGEN6C4 and EGM2008 Bouguer gravity data of 2190 degree spherical harmonic over the Singhbhum-Orissa Craton, India, have been generated from the International Centre for Global Earth Models. The Bouguer gravity anomaly difference maps of (i) in situ and EIGEN6C4, (ii) in situ and EGM2008 and iii) EIGEN6C4 and EGM2008 of the study area are compared. It reveals that EIGEN6C4 has lesser systematic error than EGM2008. However, from different profile plots of Bouguer gravity, east–west horizontal derivative and north–south horizontal derivative anomalies of the in situ, EIGEN6C4 and EGM2008, it is observed that most of the signatures of lithounits and geological structural elements are delineated very well by EGM2008 and match 94–98% with those of EIGEN6C4. Further, the Bouguer gravity, east–west horizontal derivative and north–south horizontal derivative anomalies of EGM2008 data over the study area have been used effectively for identifying various lithounits and geological structural elements.

Multispectral remote sensing for mapping grassland degradation using the key indicators of grass species and edaphic factors

Abstract: Land degradation is believed to be one of the most severe and widespread environmental problems. In South Africa, large areas of land have been identified as degraded, as shown by the lower vegetation cover. One of the major causes of grassland degradation is change in plant species composition that leads to presence of unpalatable grass species. Some grass species have been successfully used as indicators of different levels of grassland degradation in the country. This paper, therefore explores the possibility of mapping grassland degradation in Cathedral Peak, South Africa, using indicators of grass species and edaphic factors. Multispectral SPOT 5 data were used to produce a grassland degradation map based on the spatial distribution of decreaser (Themeda triandra) and increaser (Hyparrhenia hirta) species. To improve mapping accuracy, soil samples were collected from each species site and analysed for nutrient content. A t-test and machine learning random forest classification algorithm were applied ...

Monitoring of water stress in wheat using multispectral indices derived from Landsat-TM

Abstract: Detection of crop water stress is crucial for efficient irrigation water management. Potential of Satellite data to provide spatial and temporal dynamics of crop growth conditions makes it possible to monitor crop water stress at regional level. This study was conducted in parts of western Uttar Pradesh and Haryana. Multi-temporal Landsat data were used for detecting wheat crop water stress using vegetation indices (VIs), viz. vegetation water stress index (VWSI) and land surface wetness index water stress factor (Ws_LSWI). The estimated water stress from satellite data-based VIs was validated by water stress factor (Ws) derived from flux-tower data. The study observed Ws_LSWI to be better index for water stress detection. The results indicated that Ws_LSWI was superior over other index showing RMSE = 0.12, R2 = 0.65, whereas VWSI showed overestimated values with mean RD 4%.

GIS-based approach for flood analysis: case study of Kecidere flash flood event (Turkey)

Abstract: The purpose of this study is to explain the formation mechanism of the floods which occurred in the Kecidere basin in 2009. In this study, discharge data in between 1981 and 2009, digital elevation model (DEM), satellite images and field works were used as a main data sources. LPT3 was applied to 29-year maximum flow data to produce different flood return periods such as 2, 5, 50, 100, 200, 500 and 1000-year flood. The DEM was created using 1:25,000 topographic contours with Topo to Raster interpolation techniques in geographical information systems (GIS). Land use and some geometric data were digitized using high resolution satellite images for hydraulic modelling purposes. Simulation of the 2009 flash flood event and different return periods flow data was done using one-dimensional hydraulic modelling with HEC-RAS. In the last phase, results obtained from the simulations and field works were compared based on fits statistics and mean absolute error in terms of extent and depth. An analysis of water exte...

Estimation of sub-catchment area parameters for Storm Water Management Model (SWMM) using geo-informatics

Abstract: This study presents a remote sensing and geographic information systems-based approach for using US EPA’s Storm Water Management Model (SWMM) in urban environment. Cartosat-1 PAN + IRS-P6 LISS-IV merged product was used to map land cover in part of Surat city at 1:10,000 scale. Cartosat-1 stereo pair was used for deriving digital elevation model of the study area. Geo-informatics-based methods were developed for delineation of sub-catchment areas, assignment of sub-catchment outlets and estimation of characteristic width. It was observed that 59% of the developed area in the study region was directly or indirectly connected to the storm water drainage network. Furthermore, dynamic rainfall-runoff simulation on three-day rainfall indicated that the average runoff coefficient on the urbanized sub-catchment areas which were directly connected to the drainage network was 0.92 as against 0.88 on those urbanized sub-catchments without having direct access to storm water drainage.

Simulating urban growth processes by integrating cellular automata model and artificial optimization in Binhai New Area of Tianjin, China

Abstract: This study presents an optimized algorithm into the cellular automata (CA) models for urban growth simulation in Binhai New Area of Tianjin, China. The optimized CA model by particle swarm optimization (PSO) was compared with the logistic-based cellular automata (LOGIT-CA) model to see the effects of the simulation. The study evaluated the stochastic disturbance in the development of urban growth using the Monte Carlo method; the coefficient d determined the state of urban growth. The validation was conducted by both cross-tabulation test and structural measurements. The results showed that the simulations of PSO-CA were better than LOGIT-CA model, indicating an improvement in the spatio-temporal simulation of urban growth and land use changes in study area. Since the simulations reached their best values when the coefficient was between 1 and 2, the urban growth in the study area was in the period of conversion from spontaneous growth to edge-expansion and infilling growth.

Application of topo-edaphic factors and remotely sensed vegetation indices to enhance biomass estimation in a heterogeneous landscape in the Eastern Arc Mountains of Tanzania

Abstract: Estimating tropical biomass is critical for establishment of conservation inventories and landscape monitoring. However, monitoring biomass in a complex and dynamic environment using traditional methods is challenging. Recently, biomass estimates based on remotely sensed data and ecological variables have shown great potential. The present study explored the utility of remotely sensed data and topo-edaphic factors to improve biomass estimation in the Eastern Arc Mountains of Tanzania. Twenty-nine vegetation indices were calculated from RapidEye data, while topo-edaphic factors were taken from field measurements. Results showed that using topo-edaphic variables or vegetation indices, biomass could be predicted with an R2 of 0.4. A combination of topo-edaphic variables and vegetation indices improved the prediction accuracy to an R2 of 0.6. Results further showed a decrease in biomass estimates from 1162 ton ha−1 in 1980 to 285.38 ton ha−1 in 2012. This study demonstrates the value of combining remotely sen...

Revisiting cartography: towards identifying and developing a modern and comprehensive framework

Abstract: Developments in production, sharing and use of spatial data and information involve revisiting the role and scope of cartography. Cartography is a core discipline for spatially modelling, investigating and mapping natural and cultural environments, developing location-aware applications, establishing spatial data infrastructures and forming spatially enabled societies. In this context, spatial data handling provides key tools for creating spatial databases, integrating spatial data, producing geographic information and maps and so on. Although cartography plays a key role in many phases of such activities, it tends to be introduced only as visualization phase of spatial data handling. On the other hand, it is sometimes regarded to encompass entire phases of spatial data handling. So this article investigates the relationships between cartography and spatial data handling, management and use, and on this basis, proposes a modern and comprehensive framework for cartography to contribute to restoring the ful...

An experimental comparison between KELM and CART for crop classification using Landsat-8 OLI data

Abstract: The operational land imager (OLI) is the latest instrument in the Landsat series of satellite imagery, which officially began normal operations on 30 May 2013. The OLI includes two bands that are not on the thematic mapper series of sensors aboard Landsat-5 and 7; a cirrus band and a coastal/aerosol band. This paper compares the classification and regression tree and the kernel-based extreme learning machine (KELM) for mapping crops in Hokkaido, Japan, using OLI data, except the cirrus band and the pan band. The OLI data acquired on 8 July 2013 was used for crop classification of beans, beets, grassland, maize, potatoes and winter wheat. The KELM algorithm performed better in this study and achieved overall accuracies of 90.1%. According to the Jeffries–Matusita (J–M) distances, the short wavelength infrared band provides the greater contribution (the highest value was observed for band 6 in OLI data).

Remote sensing of alpine glaciers in visible and infrared wavelengths: a survey of advances and prospects

Abstract: Remote sensing is an efficient tool for temporal monitoring of inaccessible alpine glacial terrain. This study discusses the methods of remote sensing in visible and infrared (IR) wavelengths, which are helpful in providing important information about alpine glaciers. The scope of this study covers recent advances and prospects in optical and thermal remote sensing of glacier facies, glacier velocity, mass balance, glacial hazards and automated mapping techniques. The technology is ever evolving with the advent of new remote sensors capturing data in visible/IR wavelengths and better digital computing technology. An extensive list of significant studies further helps the reader to explore a particular topic of interest. We survey recent advances in this field and additionally highlight the emerging prospects.

Object-oriented semantic labelling of spectral–spatial LiDAR point cloud for urban land cover classification and buildings detection

Abstract: The urban land cover mapping and automated extraction of building boundaries is a crucial step in generating three-dimensional city models. This study proposes an object-based point cloud labelling technique to semantically label light detection and ranging (LiDAR) data captured over an urban scene. Spectral data from multispectral images are also used to complement the geometrical information from LiDAR data. Initial object primitives are created using a modified colour-based region growing technique. Multiple classifier system is then applied on the features extracted from the segments for classification and also for reducing the subjectivity involved in the selection of classifier and improving the precision of the results. The proposed methodology produces two outputs: (i) urban land cover classes and (ii) buildings masks which are further reconstructed and vectorized into three-dimensional buildings footprints. Experiments carried out on three airborne LiDAR datasets show that the proposed technique ...

Understanding the spatial distribution of elephant (Loxodonta africana) poaching incidences in the mid-Zambezi Valley, Zimbabwe using Geographic Information Systems and remote sensing

Abstract: The objective of this study was to understand the factors that explain the spatial distribution of elephant poaching activities in the areas of the mid-Zambezi Valley, Zimbabwe using geographic information system (GIS) and remotely sensed data integrated with spatial logistic regression. The results showed that significant (α = 0.05) elephant poaching hot spots are located closer to wildlife protected areas. Results further demonstrated that resource availability (water and forage) are the main factors explaining elephant poaching activities in the mid-Zambezi Valley. For example, the majority of poaching activities were found to occur in areas with high vegetation fractional cover (high forage) and close to waterholes. The results also showed that poaching incidences were more prevalent during the dry season. The findings of this study highlight the significance of integrating GIS, remotely sensed data and spatial logistic regression tools for understanding and monitoring elephant poaching activi...

Predicting forest carbon stocks from high resolution satellite data in dry forests of Zimbabwe : exploring the effect of the red-edge band in forest carbon stocks estimation

Abstract: In this study, we tested whether the inclusion of the red-edge band as a covariate to vegetation indices improves the predictive accuracy in forest carbon estimation and mapping in savanna dry forests of Zimbabwe. Initially, we tested whether and to what extent vegetation indices (simple ratio SR, soil-adjusted vegetation index and normalized difference vegetation index) derived from high spatial resolution satellite imagery (WorldView-2) predict forest carbon stocks. Next, we tested whether inclusion of reflectance in the red-edge band as a covariate to vegetation indices improve the model's accuracy in forest carbon prediction. We used simple regression analysis to determine the nature and the strength of the relationship between forest carbon stocks and remotely sensed vegetation indices. We then used multiple regression analysis to determine whether integrating vegetation indices and reflection in the red-edge band improve forest carbon prediction. Next, we mapped the spatial variation in forest carbo...

Modeling the risk of spread and establishment for Asian longhorned beetle (Anoplophora glabripennis) in Massachusetts from 2008-2009

Abstract: Land managers responsible for invasive species removal in the USA require tools to prevent the Asian longhorned beetle (Anoplophora glabripennis) (ALB) from decimating the maple-dominant hardwood forests of Massachusetts and New England. Species distribution models (SDMs) and spread models have been applied individually to predict the invasion distribution and rate of spread, but the combination of both models can increase the accuracy of predictions of species spread over time when habitat suitability is heterogeneous across landscapes. First, a SDM was fit to 2008 ALB presence-only locations. Then, a stratified spread model was generated to measure the probability of spread due to natural and human causes. Finally, the SDM and spread models were combined to evaluate the risk of ALB spread in Central Massachusetts in 2008–2009. The SDM predicted many urban locations in Central Massachusetts as having suitable environments for species establishment. The combined model shows the greatest risk of sp...

Analysis of snow cover and climatic variability in Bhaga basin located in western Himalaya

Abstract: Bhaga Basin has complex mountainous terrain; little study has been done on the spatial and temporal characteristics of snow cover in the region. The Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day snow cover products between 2001 and 2012 for winter period (November–April) have been used to study the variation in snow cover area (SCA). The statistical analysis based on non-parametric Mann Kendall and Sen’s slope methods have been used for detecting and estimating trends for climatic variables (temperature and snowfall) and SCA for winter period. Results of statistical analysis indicate rise in minimum temperature (0.02 °C year−1) and fall in maximum temperature (0.17 °C year−1). It also shows decrease in mean seasonal snowfall (0.07 cm year−1). The seasonal SCA was found to decrease at the rate of 0.002% year−1. This study indicates that the climate change is probably one of the major causes for depleting SCA.

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

Abstract: 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 Nino – 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.

Effect of slope steepness parameter computations on soil loss estimation: review of methods using GIS

Abstract: In the analysis of soil loss equation, the researchers have suggested two methods of deriving the slope steepness parameter. One method is having percentage slope term, while the other method is having sinθ as its term. In this paper, both the methods were analysed and compared in soil loss computation using Revised Universal Soil Loss Equation, over a Gangapur catchment area in India, having steep slopes. The soil loss rates derived were 0.98 million tonnes per year in case of steepness parameter derived by sinθ and 1.226 million tonnes per year in case of steepness parameter derived by percentage slope term. The observed rate of soil loss is 1.23 million tonnes per year. This methodology of soil loss estimation was also validated with similar catchment of Punegaon dam. It is concluded that for medium to steep terrain, percentage slope method estimates more accurate soil loss than other empirical methods for slope steepness estimation.

Integrated approach of using ASTER-derived emissivity and pixel temperature for delineating different granitoids – a case study in parts of Dharwar Craton, India

Abstract: We have delineated different granitoids based on variation in emissivity and relative surface temperature recorded in thermal bands of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor of EO-1 satellite. In this regard, we have used emissivity normalization algorithm to derive broadband emissivity from thermal bands of ASTER sensor to delineate different lithounits of the granitoid family. We have compared emissivity and radiance image composites in terms of delineation of different granitoids. We have also used false colour composite (FCC) image derived using two emissivity bands and temperature (derived using emissivity normalisation method) bands to delineate different granitoids. We could differentiate different granitoids in the three-dimensional (3D) data space of ASTER-derived emissivity bands (second and third bands) and temperature bands. Based on the analysis of 3D scatter plot, we also proposed a ternary diagram of emissivity and temperature, which can be use...

Analysis of the influential factors for changes to land use in China’s Xingwen Global Geopark against a tourism development background

Abstract: This study employs geographic information system software to explore the influences of elevation, slope, the river system, traffic arteries and the central development zone on the land-use changes in Shihai between 1995 and 2010. Data were drawn from statistics from the first two remote sensing investigations of land use in the town of Shihai in China’s Xingwen Global Geopark and its digital elevation model data. An analysis of the relationships between changes in land use was performed using relevant models, including a comprehensive land-use dynamic degree model, a single land-use dynamic degree model and a comprehensive index model for the extent of land use. The results suggest that a combination of natural and human factors influenced the changes in Shihai’s land use during the time from 1995 to 2010. First, elevation and slope exerted environmental resistance. Specifically, as elevation or slope increased, the extent of change in land use decreased, despite local policies that have reduced the exten...