bluuebunny/crossref_metadata_2025 huggingface dataset:
Synergistic use of Imager Window observations for Cloud Clearing of Sounder Observation for INSAT-3D
Authors: Satapathy J. , Thapliyal P. K. , Shukla M. V. , Kishtawal C. M.
Published: November 2014

Abstract. The retrieval of atmospheric temperature and water vapor profiles from infrared Sounder are severely limited by the presence of cloud. Therefore, retrieval from infrared sounding observations is performed only over clear-sky atmospheric conditions. The probability of finding a clear-sky pixel at spatial resolution of 10 km is found to be very small globally. This study presents a quantitative analysis of the clear-sky probability that is carried out for different months over the Indian region for INSAT-3D Sounder. The probability of a clear-sky is found to be ~7 % for the field of view of 10 km corresponding to the INSAT-3D Sounder. This statistical analysis is established using MODIS cloud mask having 95 % confidence level at 1 km resolution spread in the region between 50E–110E and 30S–30N. This necessitates cloud clearing to remove the effect of partial clouds in the Sounder FOV to provide a clear-sky equivalent sounding retrieval. Various methods were explored to derive the cloud-cleared radiances using supplementary information such as high resolution infrared or microwave observations. This study presents an effort to use the existing traditional method to derive optimal cloudcleared radiances for INSAT-3D Sounder, by estimating the fractional cloud cover using collocated high resolution INSAT-3D Imager window channel observation. The final Sounder cloud-cleared radiances have been validated with the operational AIRS L2 cloud-cleared radiance products. Nevertheless, the statistical analysis of clear-sky probability over Indian region also provides a significant insight towards the dependency of spatial resolution and the considerable field-of-regard (FOR) in obtaining the clear-sky area in the satellite observations. This, in a way, necessitates the cloud-clearing for coarser resolution sensors and at the same time, states the benefits of using very high resolution sensors. It has been observed that FOV of 1km and by choosing a reasonably good FOR can eliminate the cloudy-sky hindrances by increasing the probability of clear-sky from 5 % to 50 %.
Identification of prominent spatio-temporal signals in GRACE derived terrestrial water storage for India
Authors: Banerjee C. , Nagesh Kumar D.
Published: November 2014

Abstract. Fresh water is a necessity of the human civilization. But with the increasing global population, the quantity and quality of available fresh water is getting compromised. To mitigate this subliminal problem, it is essential to enhance our level of understanding about the dynamics of global and regional fresh water resources which include surface and ground water reserves. With development in remote sensing technology, traditional and much localized in-situ observations are augmented with satellite data to get a holistic picture of the terrestrial water resources. For this reason, Gravity Recovery And Climate Experiment (GRACE) satellite mission was jointly implemented by NASA and German Aerospace Research Agency – DLR to map the variation of gravitational potential, which after removing atmospheric and oceanic effects is majorly caused by changes in Terrestrial Water Storage (TWS). India also faces the challenge of rejuvenating the fast deteriorating and exhausting water resources due to the rapid urbanization. In the present study we try to identify physically meaningful major spatial and temporal patterns or signals of changes in TWS for India. TWS data set over India for a period of 90 months, from June 2003 to December 2010 is use to isolate spatial and temporal signals using Principal Component Analysis (PCA), an extensively used method in meteorological studies. To achieve better disintegration of the data into more physically meaningful components we use a blind signal separation technique, Independent Component Analysis (ICA).
Quantitative Geomorphological Analysis & Land Use/ Land Cover Change Detection of Two Sub-Watersheds in NE region of Punjab, India
Authors: Kaur M. , Singh S. , Verma V. K. , Pateriya B.
Published: November 2014

Abstract. Morphometric analysis is the measurement and mathematical analysis of the landforms. The delineation of drainage system is of utmost importance in understanding hydrological system of an area, water resource management and it's planning in an effective manner. Morphometric analysis and land use change detection of two sub-watersheds namely Kukar Suha and Ratewal of district Shahid Bhagat Singh Nagar, Punjab, India was carried out for quantitative description of drainage and characterisation. The stream order, stream number, stream length, mean stream length, and other morphometric analysis like bifurcation ratio, drainage density, texture, relief ratio, ruggedness number etc. were measured. The drainage pattern of Kukar Suha and Ratewal is mainly dendritic. The agriculture and settlements came up along the drainage network causes the pattern disturbance in the watershed. The study was undertaken to spotlight the morphometric parameters, their impact on the basin and the land use land cover changes occurred over the period of time. Morphometric parameters such as linear aspect, areal aspect and relief aspect of the watershed are computed. The land use/land cover change was extracted from LISS IV Mx + Cartosat1 PAN data. ASTER data is used to prepare DEM (digital elevation model) and geographical information system (GIS) was used to evaluate various morphometric parameters in ArcGIS10 software.
Assessment of underground water potential zones using modern geomatics technologies in Jhansi district, Uttar Pradesh, India.
Authors: Pandey N. K. , Shukla A. K. , Shukla S. , Pandey M.
Published: November 2014

Abstract. Ground water is a distinguished component of the hydrologic cycle. Surface water storage and ground water withdrawal are traditional engineering approaches which will continue to be followed in the future. The uncertainty about the occurrence, distribution and quality aspect of the ground water and the energy requirement for its withdrawal impose restriction on exploitation of ground water. The main objective of the study is assessment of underground water potential zones of Jhansi city and surrounding area, by preparing underground water potential zone map using Geographical Information System (GIS), remote sensing, and validation by underground water inventory mapping using GPS field survey done along the parts of National Highway 25 and 26 and some state highway passing through the study area. Study area covers an area of 1401 km2 and its perimeter is approximate 425 km. For this study Landsat TM (0.76–0.90 um) band data were acquired from GLCF website. Sensor spatial resolution is 30 m. Satellite image has become a standard tool aiding in the study of underground water. Extraction of different thematic layers like Land Use Land Cover (LULC), settlement, etc. can be done through unsupervised classification. The modern geometics technologies viz. remote sensing and GIS are used to produce the map that classifies the groundwater potential zone to a number of qualitative zone such as very high, high, moderate, low or very low. Thematic maps are prepared by visual interpretation of Survey of India topo-sheets and linearly enhanced Landsat TM satellite image on 1 : 50,000 scale using AutoCAD, ArcGIS 10.1 and ERDAS 11 software packages.
Satellite-based estimation and validation of monthly rainfall distribution over Upper Ganga river basin
Authors: Shukla A. K. , Ojha C. S. P. , Garg R. D.
Published: November 2014

Abstract. Water is one of the most precious natural resources for all living flora and fauna. 97.5% of water on the Earth is sea water, the remaining 2.5 % is fresh water of which slightly over two thirds is frozen in glaciers and polar ice caps. The unfrozen fresh water is mainly found as groundwater, with only a small fraction present above ground or in the air. Since one of the main source of water is rainfall. Therefore, proper information on rainfall and its variability in space and time is required for better watershed planning and management and other applications. In Himalayan basin, the rain gauge network is relatively sparse with uneven distribution. Hence, there is lack of proper information on rainfall patterns of this region. The main advantage of satellite derived rainfall estimation over rain gauge derived rain data is that these provide homogenous spatio-temporal rainfall information over a large area e.g. Upper Ganga river basin region. Therefore, a better understanding of the rainfall patterns of this region is required for better disaster mitigation. The objectives of this study are to evaluate the reliability of Tropical Rainfall Measuring Mission (TRMM) 3B43 V7 derived high resolution satellite product to study the rainfall distribution over the Upper Ganga river basin. TRMM 3B43 V7 derived monthly rainfall data is analyzed and the monthly rainfall product is validated and correlated with IMD (Indian Meteorological Department) gauge station's rainfall data. The monthly rainfall data of 15 years i.e. from 1998 to 2012 is used in the study. Statistical indices can be used to evaluate, compare and validate satellite rainfall data with respect to gauge rainfall data. Statistical indices used in this study are Correlation Coefficient (r), Mean Square Error (MSE), Root Mean Square Error (RMSE), and Average Percentage Error (Avg. % Error). Most of the rainfall in the study area occurs in the months of June, July, August, September and October. The isohyets were prepared using gauge rainfall data and are matched with the spatially distributed rainfall surface prepared from TRMM satellite data for all the months of the rainy season of the study area. Kriging spatial interpolation method was used to generate the spatially distributed rainfall surface. From the results it was observe d that they matched fairly well with each other showing high spatial correlation. The monthly rainfall result showed that TRMM data is underestimated with low accuracy, though TRMM data and rain gauge data have positive correlation.
Geospatial Techniques for Efficient Conservation and Management of Surface Water for Irrigation in Joganbedi Village, Khargone District, Madhya Pradesh, India
Authors: Singh A. M. , Chauhan A. S. , Aggarwal D.
Published: November 2014

Abstract. The study aimed at developing improved methods based on remote sensing and GIS techniques to increase cultivated area under irrigation. Landuse / landcover mapping was considered as the key component to prioritize locations for constructing appropriate recharge structures. Joganbedi scheme was proposed for this study. Joganbedi is situated 13 km. from Khargone, district Khargone, Madhya Pradesh, India. Command area of the proposed scheme lies in Beda sub-basin which is a tributary of the Narmada River. This area is of hard rock terrain and is occupied by the Deccan basalt. The main objective of the study was surface water conservation and management via multi-spectral information resulting from remotely sensed data to increase irrigation. High resolution GeoEye1 stereo images were used for generation of DEM, contour, landuse/landcover mapping, lineaments and drainage mapping. DEM was used for canal alignment. and further, contours were used to determine catchment, submergence /FRL, and command areas. Landuse/landcover statistics of submergence area helped to identify different land classes within the study area. These parameters are required for scheme planning. Additionally, rainfall data, maximum drawdown level, and dam height were collected as supporting parameters. The study concludes that landuse/landcover mapping is useful in identification of surface water conservation and management plan for irrigation purpose. It also proves that implementation of Joganbedi scheme will increase the cultivated area under irrigation, facilitate the farmers for multi season cropping and help in improving their economic condition.
Spectral stratigraphy and clay minerals analysis in parts of Hellas Planitia, Mars
Authors: Das I. C. , Joseph J. , Subramanian S. K. , Dadhwal V. K.
Published: November 2014

Abstract. Absorption features that occur in reflectance spectra are a sensitive indicator of mineralogy and chemical composition for a wide variety of materials. The investigation of the mineralogy and chemical composition of surfaces give information about the origin and evolution of planetary bodies. On Mars, the processes of formation of different types of clay minerals result from different types of wet conditions viz. hydrothermalism, subsurface/groundwater weathering, surface alteration etc. The image analyzed in the present study was frt000947f- 164-trr3 (−27.87N–65.06E). Through the spectral stratigraphic characterization along a crater wall, eight (8) different layers were identified considering the spectral variability and their position. In Hellas Planitia, the alteration minerals identified by CRISM based on distinctive absorptions from 0.4 to3.9 μm include Al-rich smectite, montmorillonite, phyllosilicate mineral at 2.2 μm and 2.35 μm, including strong absorption feature noticed at 1.9 μm. We conclude that the layers exposed in the crater wall help characterize the compositional stratigraphy for confirming the presence of hydrated minerals in this region as an outcome of geohydrological weathering process.
Extraction of aqueous minerals on Mars using CRISM based Targeted Reduced Data Records
Authors: Gurunadham R. , Kumar S.
Published: November 2014

Abstract. Many scientific studies have been carried out to extract the aqueous mineral signatures on the surface of Mars, which has a record of all minerals such as silicates form by magmatic processes and aqueous minerals in the presence of watery environment. To observe these watery conditions, a visible/shortwave infrared mineral mapping camera on Mars Reconnaissance Orbiter (MRO) called Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) is used. The aim of this research is to extract the aqueous minerals on Mars using CRISM sensor. Gale Crater is selected for this study because of its past liquid water history.Gale is ~154 km in diameter and centered near 5.3° S, 138° E. Gale Crater has an interior mound named as "Aeolis Mons", which is nearly 100 km wide and 5 km high, consisting of layered sulfates and phyllosilicates. The CRISM reflectance (I/F) targeted reduced data records data of Gale crater, FRT000233AC, centred at 4°25' S and 137°20' E with high spatial (18 m, 35 m / pixel) and spectral resolution (362–1020 nm (VNIR), 1002–3920 nm (IR), 655 nm / channel) with 545 bands is acquired for this study. The detection and quantification of minerals has been carried out by using a model called modified Gaussian model (MGM). MGM is an approach that uses modified Gaussians in wave number space to model absorption shapes and fits them to a reflectance spectrum.
Evaluation of Time Series TanDEM-X Digital Elevation Models
Authors: Jain M. , Deo R. , Kumar V. , Rao Y. S.
Published: November 2014

Abstract. Digital Elevation Model (DEM) is an important input for geo-spatial analysis. For various applications like flood management, ortho rectification of remote sensing images, navigation, architectural works, defence, etc., high resolution DEM is required. TanDEM-X mission was launched in 2010 to obtain high resolution global DEM with HTRI-3 standard. SAR interferometry (InSAR) technique is used for DEM generation from TanDEM-X SAR data. The accuracy of DEM depends on many parameters like height ambiguity, incidence angle, polarization, etc. In this study, time series TanDEM-X data spanning over 3 years, had processed for generating DEM at the spatial resolution of 6 m and their accuracy had studied using DGPS elevation data and SRTM 90 m DEM. The products generated during DEM generation process are DEM, precision (or height error), coherence, layover and shadow images. Using weighted average fusion technique, ascending and descending DEMs are fused for improving the quality of DEM and to reduce invalid pixels corresponding to layover and shadow areas. Results from time series data were analysed and found RMSE error of fused DEMs is in the range of 2 m to 4 m, while individual DEM has accuracy of 3 m to 6 m with respect to DGPS elevation data. Fused DEMs are having high accuracy as well as less voids. The reduction of voids by fusion, ranges from 40 to 85 % in different combinations of data.
A Unified Framework for Dimensionality Reduction and Classification of Hyperspectral Data
Authors: Kolluru P. , Pandey K. , Padalia H.
Published: November 2014

Abstract. The processing of hyperspectral remote sensing data, for information retrieval, is challenging due to its higher dimensionality. Machine learning based algorithms such as Support Vector Machine (SVM) is preferably applied to perform classification of high dimensionality data. A single-step unified framework is required which could decide the intrinsic dimensionality of data and achieve higher classification accuracy using SVM. This work present development of a SVM-based dimensionality reduction and classification (SVMDRC) framework for hyperspectral data. The proposed unified framework was tested at Los Tollos in Rodalquilar district of Spain, which have predominance of alunite, kaolinite, and illite minerals with sparse vegetation cover. Summer season image was utilized for implementing the proposed method. Modified broken stick rule (MBSR) was used to calculate the intrinsic dimensionality of HyMap data which automatically reduce the number of bands. Comparison of SVMDRC with SVM clearly suggests that SVM alone is inadequate in yielding better classification accuracies for minerals from hyperspectral data rather requires dimensionality reduction. Incorporation of modified broken stick method in SVMDRC framework positively influenced the feature separability and provided better classification accuracy. The mineral distribution map produced for the study area would be useful for refining the areas for mineral exploration.
Sub pixel location identification using super resolved multilooking CHRIS data
Authors: Sahithi V. S. , Agrawal S.
Published: November 2014

Abstract. CHRIS /Proba is a multiviewing hyperspectral sensor that monitors the earth in five different zenith angles +55°, +36°, nadir, −36° and −55° with a spatial resolution of 17 m and within a spectral range of 400–1050 nm in mode 3. These multiviewing images are suitable for constructing a super resolved high resolution image that can reveal the mixed pixel of the hyperspectral image. In the present work, an attempt is made to find the location of various features constituted within the 17m mixed pixel of the CHRIS image using various super resolution reconstruction techniques. Four different super resolution reconstruction techniques namely interpolation, iterative back projection, projection on to convex sets (POCS) and robust super resolution were tried on the −36, nadir and +36 images to construct a super resolved high resolution 5.6 m image. The results of super resolution reconstruction were compared with the scaled nadir image and bicubic convoluted image for comparision of the spatial and spectral property preservance. A support vector machine classification of the best super resolved high resolution image was performed to analyse the location of the sub pixel features. Validation of the obtained results was performed using the spectral unmixing fraction images and the 5.6 m classified LISS IV image.
The role of national and international geospatial data sources in the management of natural disasters
Authors: Kayi A. , Erdogan M. , Yilmaz A.
Published: November 2014

Abstract. An earthquake occurred at Van City on 23 October 2011 at 13:41 local time. The magnitude, moment magnitude and depth of earthquake were respectively MI:6.7, Mw:7.0 and 19.07 km. Van city centre and its surrounding villages were affected from this destructive earthquake. Many buildings were ruined and approximately 600 people died. Acquisition and use of geospatial data is very important and crucial for the management of such kind of natural disasters. In this paper, the role of national and international geospatial data in the management of Van earthquake is investigated.. With an international collaboration with Charter, pre and post-earthquake satellite images were acquired in 24 hours following the Earthquake. Also General Command of Mapping (GCM), the national mapping agency of Turkey, produced the high resolution multispectral orthophotos of the region. Charter presented the orthophotos through 26–28 October 2012. Just after the earthquake with a quick reaction, GCM made the flight planning of the 1296 km2 disaster area to acquire aerial photos. The aerial photos were acquired on 24 October 2012 (one day after the earthquake) by UltraCamX large format digital aerial camera. 152 images were taken with 30 cm ground sample distance (GSD) by %30 sidelap and %60 overlap. In the evening of same flight day, orthophotos were produced without ground control points by direct georeferencing and GCM supplied the orthophotos to the disaster management authorities. Also 45 cm GSD archive orthophotos, acquired in 2010, were used as a reference in order to find out the effects of the disaster. The subjects written here do not represent the ideas of Turkish Armed Forces.
Comparative Analysis of Hyperspectral and Multispectral Data for Mapping Snow Cover and Snow Grain Size
Authors: Anul Haq M.
Published: November 2014

Abstract. The present study demonstrates the potential of imaging spectroscopy to produce the snow cover maps and estimation of snow grain size in the Himalayan region. Snow cover maps and snow grain size produce from imaging spectroscopy data were also compared with multispectral imagery (i.e. Landsat 8 and ASTER). Snow grain size was estimated using the snow grain index and compared with the asymptotic radiative transfer (ART) theory method. The overall matching area was 78.29 % among different snow grain size classes using grain index Method and ART method. An attempt has been made to derive the snow grain size using Landsat 8 and ASTER data for the same area. It was found that grain size derived from Landsat 8 and ASTER data show correlation of 81.67 % and 86.34 % respectively. The snow cover maps were produced using Normalized Difference Snow Index (NDSI). Snow cover maps were also produced using ASTER imagery for the same area and compared with Hyperion snow cover maps. The correlation between both snow cover maps were show 91 % correlation.
Comparison of energy balance on Gangotri and Chhota Shigri Glaciers
Authors: Rastogi G. ,   Ajai
Published: November 2014

Abstract. Surface energy balance of a glacier governs the physical processes taking place at the surface-atmosphere interface and connects ice ablation/accumulation to climate variability. To understand the response of Himalayan glaciers to climatic variability, a study was taken to formulate energy balance equation on two of the Indian Himalayan glaciers, one each from Indus and Ganga basins, which have different climatic and physiographic conditions. Study was carried out over Gangotri glacier (Ganga basin) and Chhota Shigri(CS) glacier from Chandra sub-basin (Indus basin). Gangotri glacier is one of the largest glaciers in the central Himalaya located in Uttarkashi District, Uttarakhand, India. Chhota Shigri glacier of Chandra sub-basin lies in Lahaul and Spiti valley of Himachal Pradesh. Energy balance components have been computed using inputs derived from satellite data, AWS (Automatic Weather Station) data and field measurements. Different components of energy balance computed are net radiation (includes net shortwave and net longwave radiation), sensible heat flux and latent heat flux. In this study comparison has been made for each of the above energy balance components as well as total energy for the above glaciers for the months of November and December, 2011. It is observed that net radiation in Gangotri glacier is higher by approximately 43 % in comparison to Chhota Shigri glacier; Sensible heat flux is lesser by 77 %; Latent heat flux is higher by 66 % in the month of November 2011. Comparison in the month of December shows that net radiation in Gangotri glacier is higher by approximately 22 % from Chhota Shigri glacier; Sensible heat flux is lesser by 90 %; Latent heat flux is higher by 3 %.Total energy received at the glacier surface and contributes for melting is estimated to be around 32 % higher in Gangotri than Chhota Shigri glacier in November, 2011 and 1.25 % higher in December, 2011. The overall results contribute towards higher melting rate in November and December, 2011 in Gangotri than Chhota Shigri glacier.
Prioritising Carbon Sequestration Areas in Southern Queensland using Time Series MODIS Net Primary Productivity (NPP) Imagery
Authors: Apan A. , Suarez Cadavid L. A. , Richardson L. , Maraseni T.
Published: November 2014

Abstract. The aim of this study was to develop a method that will use satellite imagery to identify areas of high forest growth and productivity, as a primary input in prioritising revegetation sites for carbon sequestration. Using the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data, this study analysed the annual net primary production (NPP) values (gC/m2) of images acquired from 2000 to 2013, covering the Condamine Catchment in southeast Queensland, Australia. With the analysis of annual rainfall data during the same period, three transitions of "normal to dry" years were identified to represent the future climate scenario considered in this study. The difference in the corresponding NPP values for each year was calculated, and subsequently averaged to the get the "Mean of Annual NPP Difference" (MAND) map. This layer identified the areas with increased net primary production despite the drought condition in those years. Combined with key thematic maps (i.e. regional ecosystems, land use, and tree canopy cover), the priority areas were mapped. The results have shown that there are over 42 regional ecosystem (RE) types in the study area that exhibited positive vegetation growth and productivity despite the decrease in annual rainfall. However, seven (7) of these RE types represents the majority (79 %) of the total high productivity area. A total of 10,736 ha were mapped as priority revegetation areas. This study demonstrated the use of MODIS-NPP imagery to map vegetation with high carbon sequestration rates necessary in prioritising revegetation sites.
Assessment of net primary productivity over India using Indian geostationary satellite (INSAT-3A) data
Authors: Goroshi S. K. , Singh R. P. , Pradhan R. , Parihar J. S.
Published: November 2014

Abstract. Polar orbiting satellites (MODIS and SPOT) have been commonly used to measure terrestrial Net Primary Productivity (NPP) at regional/global scale. Charge Coupled Device (CCD) instrument on geostationary INSAT-3A platform provides a unique opportunity for continuous monitoring of ecosystem pattern and process study. An improved Carnegie-Ames-Stanford Approach (iCASA) model is one of the most expedient and precise ecosystem models to estimate terrestrial NPP. In this paper, an assessment of terrestrial NPP over India was carried out using the iCASA ecosystem model based on the INSAT CCD derived Normalized Difference Vegetation Index (NDVI) with multisource meteorological data for the year 2009. NPP estimated from the INSAT CCD followed the characteristic growth profile of most of the vegetation types in the country. NPP attained maximum during August and September, while minimum in April. Annual NPP for different vegetation types varied from 1104.55 gC m−2 year−1 (evergreen broadleaf forest) to 231.9 gC m−2 year−1 (grassland) with an average NPP of 590 gC m−2 year−1. We estimated 1.9 PgC of net carbon fixation over Indian landmass in 2009. Biome level comparison between INSAT derived NPP and MODIS NPP indicated a good agreement with the Willmott’s index of agreement (d) ranging from 0.61 (Mixed forest) to 0.99 (Open Shrubland). Our findings are consistent with the earlier NPP studies in India and indicate that INSAT derived NPP has the capability to detect spatial and temporal variability of terrestrial NPP over a wide range of terrestrial ecosystems in India. Thus INSAT-3A data can be used as one of the potential satellite data source for accurate biome level carbon estimation in India.
GIS based Cadastral level Forest Information System using World View-II data in Bir Hisar (Haryana)
Authors: Mothi Kumar K. E. , Singh S. , Attri P. , Kumar R. , Kumar A. ,   Sarika, Hooda R. S. , Sapra R. K. , Garg V. , Kumar V. ,   Nivedita
Published: November 2014

Abstract. Identification and demarcation of Forest lands on the ground remains a major challenge in Forest administration and management. Cadastral forest mapping deals with forestlands boundary delineation and their associated characterization (forest/non forest). The present study is an application of high resolution World View-II data for digitization of Protected Forest boundary at cadastral level with integration of Records of Right (ROR) data. Cadastral vector data was generated by digitization of spatial data using scanned mussavies in ArcGIS environment. Ortho-images were created from World View-II digital stereo data with Universal Transverse Mercator coordinate system with WGS 84 datum. Cadastral vector data of Bir Hisar (Hisar district, Haryana) and adjacent villages was spatially adjusted over ortho-image using ArcGIS software. Edge matching of village boundaries was done with respect to khasra boundaries of individual village. The notified forest grids were identified on ortho-image and grid vector data was extracted from georeferenced cadastral data. Cadastral forest boundary vectors were digitized from ortho-images. Accuracy of cadastral data was checked by comparison of randomly selected geo-coordinates points, tie lines and boundary measurements of randomly selected parcels generated from image data set with that of actual field measurements. Area comparison was done between cadastral map area, the image map area and RoR area. The area covered under Protected Forest was compared with ROR data and within an accuracy of less than 1 % from ROR area was accepted. The methodology presented in this paper is useful to update the cadastral forest maps. The produced GIS databases and large-scale Forest Maps may serve as a data foundation towards a land register of forests. The study introduces the use of very high resolution satellite data to develop a method for cadastral surveying through on - screen digitization in a less time as compared to the old fashioned cadastral parcel boundaries surveying method.
Application of remote sensing and GIS in land use/land cover mapping and change detection in Shasha forest reserve, Nigeria
Authors: Olokeogun O. S. , Iyiola K. , Iyiola O. F.
Published: November 2014

Abstract. Mapping of LULC and change detection using remote sensing and GIS techniques is a cost effective method of obtaining a clear understanding of the land cover alteration processes due to land use change and their consequences. This research focused on assessing landscape transformation in Shasha Forest Reserve, over an 18 year period. LANDSAT Satellite imageries (of 30 m resolution) covering the area at two epochs were characterized into five classes (Water Body, Forest Reserve, Built up Area, Vegetation, and Farmland) and classification performs with maximum likelihood algorithm, which resulted in the classes of each land use. The result of the comparison of the two classified images showed that vegetation (degraded forest) has increased by 30.96 %, farmland cover increased by 22.82 % and built up area by 3.09 %. Forest reserve however, has decreased significantly by 46.12 % during the period. This research highlights the increasing rate of modification of forest ecosystem by anthropogebic activities and the need to apprehend the situation to ensure sustainable forest management.
Decadal forest cover loss analysis over Indian forests using MODIS 250m imagery
Authors: Suraj Reddy R. , Srivastava G. , Rajashekar G. , Jha C. S. , Dadhwal V. K.
Published: November 2014

Abstract. India is endowed with a rich forest cover. Over 21 % of country's area is covered by forest of varied composition and structure. Due to large amount of carbon stored in forests and their role in land surface and climatic processes, it is important to monitor forests for effective management and modeling studies. The disturbance regimes associated with forest regeneration and recovery, occurring in a heterogeneous matrix of confounding land covers makes forest monitoring an involved and complex task. Over a 13 year period (2000–2013), detection of forest cover loss at regional scale using a coarse resolution imaging sensor (MODIS −250m) in Indian forests is attempted in the present study. MODIS provides a rich basis for forest cover monitoring at regional scales on an interannual to decadal timescales due its huge database and high temporal frequency. Forest cover loss across different forest types in parts of Maharashtra, Odisha, Chhattisgarh and Telangana states were identified using a forest-likelihood and a multi-thresholding approach. The study reveals that considerable amount of deforested patches exist over the study areas during the 2000 to 2013. Results also suggested that the detection accuracy improved with the increase of fraction of deforestation in the MODIS pixel, but still relatively small changes were also detected.
Analysis of carbon and nutrient storage of dry tropical forest of chhattisgarh using satellite data
Authors: Thakur T. K.
Published: November 2014

Abstract. The purpose of this study was to characterize the carbon, nitrogen, phosphorus and potassium in the Barnowpara Sanctuary, Raipur district, Chhattisgarh, India through the use of satellite remote sensing and GIS The total storage of nutrients in vegetation (OS + US + GS) varied from 105.1 to 560.69 kg ha−1 in N, 4.09 kg ha−1 to 49.59 kg ha−1 in P, 24.59 kg ha−1 to 255.58 kg ha−1 for K and 7310 to 4836 kg ha−1 for C in different forest types. They were highest in Dense mixed forest and lowest in Degraded mixed forest. The study also showed that NDVI and carbon storage was strongly correlated to Shannon Index and species richness thus it indicates that the diversity of forest type play a vital role in carbon accumulation. The study also developed reliable regression model for the estimation of LAI, biomass, NPP, C & N storage in dry tropical forests by using NDVI and different vegetation indices, which can be derived from fine resolution satellite data. The study shows that dry tropical forests of Central India are quite immature and not in standing state and have strong potential for carbon sequestration. Both quantitative and qualitative information derived in the study helped in evolving key strategies for maintaining existing C pools and also improving the C sequestration in different forest types. The study explores the scope and potential of dry tropical forests for improving C sequestration and mitigating the global warming and climatic change.
Relationship between AWiFS derived Spectral Vegetation Indices with Simulated Wheat Yield Attributes in Sirsa district of Haryana
Authors: Biswal A. , Sahay B. , Ramana K. V. , Rao S. V. C. K. , Sesha Sai M. V. R.
Published: November 2014

Abstract. Satellite remote sensing can provide information on plant status for large regions with high temporal resolution and proved as a potential tool for decision support. It allows accounting for spatial and temporal variations of state and driving variables, influencing crop growth and development, without extensive ground surveys. The crop phenological development and condition can be monitored through multi-temporal reflectance profiles or multi-temporal vegetation indices (VI), such as the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI). At the same time, Process based dynamic crop growth simulation models are useful tools for estimating crop growth condition and yield on large spatial domains if their parameters and initial conditions are known for each point. Therefore, combined approaches integrating remote sensing and dynamic crop growth models for regional yield prediction have been developed in several studies. In these models the vegetation state variables, e.g., development phase, dry mass, LAI are linked to driving variables, e.g., weather condition, nutrient availability and management practices. Output of these models is usually final yield or accumulated biomass. The model outputs are a summary containing an overview of the main development events, water and nitrogen variables, yield and yield components. In the present work, IRS P6 AWiFS derived vegetation indices like NDVI and NDWI are computed to study the growth profile of wheat crop in Sirsa district of Haryana along with crop growth simulation model DSSAT-CERES from 2008–09 to 2012–13.several iteration of wheat crop simulation are carried out with four sowing dates and four soil types varying with respect to the fertility parameters to represent the average simulation environment of Sirsa district in Haryana state of India. Four years time series NDVI and NDWI are used to establish the correlation between the spectral vegetation indices and simulated wheat yield attributes at critical growth stages of wheat. This work is a basic investigation towards assimilation of remote sensing derived state variables in to the crop growth model.
Enabling heterogenous multi-scale database for emergency service functions through geoinformation technologies
Authors: Bhanumurthy V. , Venugopala Rao K. , Srinivasa Rao S. , Ram Mohan Rao K. , Satya Chandra P. , Vidhyasagar J. , Diwakar P. G. , Dadhwal V. K.
Published: November 2014

Abstract. Geographical Information Science (GIS) is now graduated from traditional desktop system to Internet system. Internet GIS is emerging as one of the most promising technologies for addressing Emergency Management. Web services with different privileges are playing an important role in dissemination of the emergency services to the decision makers. Spatial database is one of the most important components in the successful implementation of Emergency Management. It contains spatial data in the form of raster, vector, linked with non-spatial information. Comprehensive data is required to handle emergency situation in different phases. These database elements comprise core data, hazard specific data, corresponding attribute data, and live data coming from the remote locations. Core data sets are minimum required data including base, thematic, infrastructure layers to handle disasters. Disaster specific information is required to handle a particular disaster situation like flood, cyclone, forest fire, earth quake, land slide, drought. In addition to this Emergency Management require many types of data with spatial and temporal attributes that should be made available to the key players in the right format at right time. The vector database needs to be complemented with required resolution satellite imagery for visualisation and analysis in disaster management. Therefore, the database is interconnected and comprehensive to meet the requirement of an Emergency Management. This kind of integrated, comprehensive and structured database with appropriate information is required to obtain right information at right time for the right people. However, building spatial database for Emergency Management is a challenging task because of the key issues such as availability of data, sharing policies, compatible geospatial standards, data interoperability etc. Therefore, to facilitate using, sharing, and integrating the spatial data, there is a need to define standards to build emergency database systems. These include aspects such as i) data integration procedures namely standard coding scheme, schema, meta data format, spatial format ii) database organisation mechanism covering data management, catalogues, data models iii) database dissemination through a suitable environment, as a standard service for effective service dissemination. National Database for Emergency Management (NDEM) is such a comprehensive database for addressing disasters in India at the national level. This paper explains standards for integrating, organising the multi-scale and multi-source data with effective emergency response using customized user interfaces for NDEM. It presents standard procedure for building comprehensive emergency information systems for enabling emergency specific functions through geospatial technologies.
Dynamics and forecasting of population growth and urban expansion in Srinagar City – A Geospatial Approach
Authors: Farooq M. , Muslim M.
Published: November 2014

Abstract. The urban areas of developing countries are densely populated and need the use of sophisticated monitoring systems, such as remote sensing and geographical information systems (GIS). The urban sprawl of a city is best understood by studying the dynamics of LULC change which can be easily generated by using sequential satellite images, required for the prediction of urban growth. Multivariate statistical techniques and regression models have been used to establish the relationship between the urban growth and its causative factors and for forecast of the population growth and urban expansion. In Srinagar city, one of the fastest growing metropolitan cities situated in Jammu and Kashmir State of India, sprawl is taking its toll on the natural resources at an alarming pace. The present study was carried over a period of 40 years (1971–2011), to understand the dynamics of spatial and temporal variability of urban sprawl. The results reveal that built-up area has increased by 585.08 % while as the population has increased by 214.75 %. The forecast showed an increase of 246.84 km2 in built-up area which exceeds the overall carrying capacity of the city. The most common conversions were also evaluated.
Influence of Agricultural Developments on Net Primary Productivity (NPP) in the Semi-arid Region of India: A Study using GloPEM Model
Authors: Gholkar M. D. , Goroshi S. , Singh R. P. , Parihar J. S.
Published: November 2014

Abstract. The present study aims to assess the effect of agricultural developments on inter-annual variations in the agricultural Net Primary Productivity (NPP) of selected districts of the semi-arid region of India by using GloPEM model. Advancements in farming practices have been contributing to the increase of net primary productivity, which ultimately leads to increase in the agricultural production. The study shows that increase in the gross irrigated area, fertilizer consumption, use of high yielding crop varieties and adoption of agricultural mechanization in terms of tractors and irrigation pumps have contributed significantly in the increase in agricultural NPP in the semi-arid region of India. The agricultural NPP of the semi-arid region of India has shown a very good correlation with the gross irrigated area (R2 = 0.668) and fertilizer use (R2 = 0.701). The anthropogenic factors influencing the agricultural NPP were grouped in 3 major Factor Components (FC) (eigenvalues > 1) as: FC1-nutrients application, FC2-irrigation potential and agricultural mechanization (irrigation pumps and tractors) and irrigated area while FC3-cultivated area and area under high yielding crop varieties. The study showed that most of the semi-arid region of India has a good agricultural production potential which needs to harness by increasing the supply of irrigation water, promoting agricultural mechanization and adoption of integrated nutrient management approach.
Radar backscattering measurement of bare soil and vegetation covered soil using X-band and full polarization
Authors: Goswami B. , Kalita M.
Published: November 2014

Abstract. The objective of the study is to measure backscattered power of bare soil and vegetation covered soil using X-band scatterometer system with full polarization and various angles during monsoon season and relate backscattered power to the density of vegetation over soil. The measurement was conducted at an experimental field located in the campus of Assam Engineering College, Guwahati, India. The soil sample consists of Silt and Clay in higher proportions as compared to Sand. The scatterometer system consists of dual-polarimetric square horn antennas, Power meter, Klystron, coaxial cables, isolator and waveguide detector. The polarization of the horn antennas as well as the look angle can be changed in the set-up. The backscattering coefficients were calculated by applying a radar equation for the measured values at incident angles between 30° and 60° for full polarization (HH, VV, HV, VH), respectively, and compared with vegetation cover over soil for each scatterometer measurement simultaneously. The VH polarization and 60° look angle are found to be the most suitable combination of configuration of an X-band scatterometer for distinguishing the land cover targets such as bare soil and vegetation covered soil. From the analysis of the results, polarimetric scatterometer data appear to be promising to distinguish the land cover types such as bare soil and soil completely covered by vegetation. The results of this study will help the scientists working in the field of active microwave remote sensing.
Role of Polarimetric SAR data for discrimination/biophysical parameters of crops based on canopy architecture
Authors: Haldar D. , Chakraborty M. , Manjunath K. R. , Parihar J. S.
Published: November 2014

Abstract. Synthetic Aperture Radar (SAR) sensors have great potential for a wide range of agricultural applications, owing to their capability of all-weather observation. It is particularly useful in tropical regions in Asia where most of the crops are grown in rainy season. The use of SAR images for the assessment of rice-planted area is in operational stage in Asian countries owing to its characteristic temporal signature however, applications of SAR images for the estimation of biophysical plant variables are challenging, especially for crop scattering and discrimination in case of other tropical crops. Canopy geometry and architecture mainly govern the interaction of microwave signal with the vegetation. In this study evaluation of C-band SAR data at different polarization combinations in linear as well as circular polarimetric imaging modes for rabi crops and other associated landuse has been attempted. Also understanding the scattering response of various crops based on canopy architecture was attempted. The scattering parameters were found to vary for planofiles and erectophiles, partitioning of scattering and absorption were determined.
Climate Change for Agriculture, Forest Cover and 3d Urban Models
Authors: Kapoor M. , Bassir D.
Published: November 2014

Abstract. This research demonstrates the important role of the remote sensing in finding out the different parameters behind the agricultural crop change, forest cover and urban 3D models. Standalone software is developed to view and analysis the different factors effecting the change in crop productions. Open-source libraries from the Open Source Geospatial Foundation have been used for the development of the shape-file viewer. Software can be used to get the attribute information, scale, zoom in/out and pan the shapefiles. Environmental changes due to pollution and population that are increasing the urbanisation and decreasing the forest cover on the earth. Satellite imagery such as Landsat 5(1984) to Landsat TRIS/8 (2014), Landsat Data Continuity Mission (LDCM) and NDVI are used to analyse the different parameters that are effecting the agricultural crop production change and forest change. It is advisable for the development of good quality of NDVI and forest cover maps to use data collected from the same processing methods for the complete region. Management practices have been developed from the analysed data for the betterment of the crop and saving the forest cover