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Assessment of temporal dynamics of snow cover and its validation with hydro-meteorological data in parts of Chenab Basin, western Himalayas

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Science China Earth Sciences 2016年第5期59卷 1081-1094页

作者： Retinder KOUR nilanchal patel Akhouri Pramod KRISHNA Department of Remote Sensing Birla Institute of Technology Mesra

The present investigation was conducted to analyze the temporal patterns of snow cover area%(SCA%), air temperature, snowfall and river discharge in parts of Chenab basin, western Himalayas. The relationship of mean SCA% with mean air temperature and river discharge was also tested using Pearson's product-moment correlation at 95% confidence limit and further sensitivity analysis of river discharge to SCA and SCA to air temperature was performed. Moderate Resolution Imaging Spectroradiometer(MODIS) 8-day surface reflectance product MOD09A1 was used to delineate SCA during the period 2000–2013. Moreover, variation in the lowest elevation from where snow cover area starts(LESCA) was also analyzed and its relationship with mean air temperature was also studied. Non-parametric method, Mann-Kendall test was employed to determine the trend in the SCA%, air temperature, snowfall and river discharge. The investigation carried out for three meteorological stations i.e. Batote, Reasi and Tandi revealed significant findings. At Batote and Reasi, statistically significant decreasing trends were observed over the period 2000 to 2012, for maximum, minimum and mean air temperature. Mean minimum SCA% exhibited a significant upward trend during 2000–2013 which is corroborated by the significantly increasing trend of mean annual snowfall(Tandi station) from 2000 to 2010. Further, significant decreasing trend of river discharge for the winter season at Batote station from 2000 to 2011 and decreasing trends in the maximum, minimum and mean air temperature at Batote and Reasi stations are also consistent with the increasing trend of SCA%. At both Batote and Reasi stations, mean SCA% exhibited significant negative relationship with the mean air temperature. On the other hand, LESCA exhibited positive correlation with the mean air temperature except in a few months, where negative relationship was seen. Sensitivity analysis of river discharge to SCA exhibited very low values of sensitivit

关键词： Chenab basin SCA Mann-Kendall test MODIS Western Himalayas Sensitivity analysis

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Comparative Assessment of the Relationship of Satellite Data with the Above Ground Biomass of Sal Trees(Shorea robusta) Determined from Phenologically Different Time Periods

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Geo-Spatial Information Science 2011年第3期14卷 177-183页

作者： nilanchal patel Arnab Majumdar Department of Remote Sensing Birla Institute of Technology Mesra

The Above Ground Biomass(AGB) estimates of vegetation comprise both the bole biomass determined through a volumetric equation and litter biomass collected from the *** mature trees,the AGB estimated in phenologically different time periods is directly affected by the litter biomass since the Diameter at Breast Height(DBH) and height(H) of such trees that are used in the estimation of bole biomass would remain unchanged over a reasonable time *** the present study,we have determined the AGB of Sal trees(Shorea robusta) in two contrasting seasons:the peak green period in October being devoid of lit-ter on the ground and the leaf shedding period in February with abundant amount of litter present on the *** of AGB for the month of February included the litter *** contrast,the AGB for October represented only the bole *** was estimated for ten different plots selected in the study *** AGB estimated from ten sampling plots for each time period was re-gressed with the individual tree parameters such as the average DBH and height of trees measured from the corresponding *** regression analysis exhibited a significantly stronger relationship between the AGB and DBH for the month of October as compared to ***,the correlation between the remotely sensed derived data and AGB was also found to be significantly higher for the month of October than *** observation indicates that inclusion of the litter biomass in AGB will tend to decrease the re-gression relationship between AGB and DBH and also between the remotely sensed data and ***,these conclusions invite careful consideration while estimating AGB from satellite data in phenologically different time periods.

关键词： above ground biomass bole biomass diameter at breast height litter biomass remotely sensed data

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Improvement of User's Accuracy Through Classification of Principal Component Images and Stacked Temporal Images

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Geo-Spatial Information Science 2010年第4期13卷 243-248页

作者： nilanchal patel Brijesh Kumar Kaushal Department of Remote Sensing Birla Institute of Technology Mesra

The classification accuracy of the various categories on the classified remotely sensed images are usually evaluated by two different measures of accuracy, namely, producer＇s accuracy （PA） and user＇s accuracy （UA）. The PA of a category indicates to what extent the reference pixels of the category are correctly classified, whereas the UA of a category represents to what extent the other categories are less misclassified into the category in question. Therefore, the UA of the various categories determines the reliability of their interpretation on the classified image and is more important to the analyst than the PA. The present investigation has been performed in order to determine if there occurs improvement in the UA of the various categories on the classified image of the principal components of the original bands and on the classified image of the stacked image of two different years. We performed the analyses using the IRS LISS Ⅲ images of two different years, i.e., 1996 and 2009, that represent the different magnitude of urbanization and the stacked image of these two years pertaining to Ranchi area, Jharkhand, India, with a view to assessing the impacts of urbanization on the UA of the different categories. The results of the investigation demonstrated that there occurs significant improvement in the UA of the impervious categories in the classified image of the stacked image, which is attributable to the aggregation of the spectral information from twice the number of bands from two different years. On the other hand, the classified image of the principal components did not show any improvement in the UA as compared to the original images.

关键词： producer's accuracy user's accuracy principal components classification stacked image

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Classification of features selected through Optimum Index Factor (OIF) for improving classification accuracy

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Journal of Forestry Research 2011年第1期22卷 99-105页

作者： nilanchal patel Brijesh Kaushal Department of Remote Sensing Birla Institute of Technology Mesra Ranchi - 835215 Jharkhand India

The present investigation was performed to determine if the features selected through Optimum Index Factor （OIF） could provide improved classification accuracy of the various categories on the satellite images of the individual years as well as stacked images of two different years as compared to all the features considered together. Further, in order to determine if there occurs increase in the classification accuracy of the different categories with corresponding increase in the OIF values of the features extracted from both the individual years＇ and stacked images, we performed linear regression between the producer＇s accuracy （PA） of the various categories with the OIF values of the different combinations of the features. The investigations demonstrated that there occurs significant improvement in the PA of two impervious categories viz. moderate built-up and low density built-up determined from the classification of the bands and principal components associated with the highest OIF value as compared to all the bands and principal components for both the individual years＇ and stacked images respectively. Regression analyses exhibited positive trends between the regression coeffi- cients and OIF values for the various categories determined for the individual years＇ and stacked images respectively signifying the prevalence of direct relationship between the increase in the information content with corresponding increase in the OIF values. The research proved that features extracted through OIF from both the individual years＇ and stacked images are capable of providing significantly improved PA as compared to all the features pooled together.

关键词： OIF supervised classification principal components band combinations

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FRACTAL ANALYSIS APPLIED TO SPATIAL STRUCTURE OF CHINA'S VEGETATION

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Chinese Geographical Science 2006年第1期16卷 48-55页

作者： ZHU Xiao-hua patel nilanchal ZUO Wei YANG Xiu-chun Institute of Geographical Sciences and Natured Resou rces Research Chinese Academy of Sciences Beijing 100101 P. R. China Department of Remote Sensing Birla Institute of Technology Ranchi 835215 India Sinomaps Press Beijing 100054 P. R. China Institute of Agricultural Resources and Regional Plaaning Chinese Academy of Agricultural Sciences Beijing 100081 P. R. China

Based on the fractal theory, the spatial structure of China＇s vegetation has been analyzed quantitatively in this paper. Some conclusions are drawn as the following. 1） The relationships between size and frequency of patch area and patch shape index exist objectively for China＇s vegetation. 2） The relationships between perimeter and area exist objectively for China＇s vegetation. 3） The fractal dimension of evergreen needleleaf forests on mountains in subtropical and tropical zones is the largest, while the smallest for deciduous broadleafand evergreen needleleaf mixed forests in temperate zone, reflecting the most complex spatial structure for evergreen needleleaf forests on mountains in subtropical and tropical zones and the simplest for deciduous broadleaf and evergreen needleleaf mixed forests in temperate zone. 4） The fractal dimensions of China＇s vegetation types tend to decrease from thc subtropics to both sides. 5） The stability of spatial structure of deciduous broadleaf and evergreen needleleaf mixed forests in temperate zone is the largest, while the smallest for double-cropping rice, or double-cropping rice and temperate-like grain, and tropical evergreen economic tree plantations and orchards, reflecting the steadiest for deciduous broadleaf and evergreen needleleaf mixed forests in temperate zone and the most unstable for double-cropping rice, or double-cropping rice and temperate-like grain, and tropical evergreen economic tree plantations and orchards in spatial structure. 6） The stability of spatial structure of China＇s vegetation tends to decrease from the temperate zone to both sides, it is significantly pertinent to understand the formation, evolution, dynamics and complexity rule of ecosystem of vegetation.

关键词： vegetation spatial structure fractal fractal dimension China

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Biomass estimation of Shorea robusta with principal component analysis of satellite data

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Journal of Forestry Research 2010年第4期21卷 469-474,524页

作者： nilanchal patel Arnab Majumdar Birla Institute of Technology Mesra

Spatio-temporal assessment of the above ground biomass （AGB） is a cumbersome task due to the difficulties associated with the measurement of different tree parameters such as girth at breast height and height of trees. The present research was conducted in the campus of Birla Institute of Technology, Mesra, Ranchi, India, which is predomi- nantly covered by Sal （Shorea robusta C. F. Gaertn）. Two methods of regression analysis was employed to determine the potential of remote sensing parameters with the AGB measured in the field such as linear regression analysis between the AGB and the individual bands, principal components （PCs） of the bands, vegetation indices （VI）, and the PCs of the VIs respectively and multiple linear regression （MLR） analysis be- tween the AGB and all the variables in each category of data. From the linear regression analysis, it was found that only the NDVI exhibited regression coefficient value above 0.80 with the remaining parameters showing very low values. On the other hand, the MLR based analysis revealed significantly improved results as evidenced by the occurrence of very high correlation coefficient values of greater than 0.90 determined between the computed AGB from the MLR equations and field-estimated AGB thereby ascertaining their superiority in providing reliable estimates of AGB. The highest correlation coefficient of 0.99 is found with the MLR involving PCs of VIs.

关键词： above ground biomass spectral response modeling vegetation indices principal component analysis linear and multiple regression analysis.

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