Prem Chandra Pandey

Assessment of land consumption rate with urban dynamics change using geospatial techniques

Land consumption is increasing rapidly with the exponential growth of population. The built-up environment configuration influences the management processes for development and other municipality works. Population growth also affects the availability of land for different purposes in its spatial distribution. The present study was conducted using satellite remote sensing data Landsat MSS (Multi-spectral Scanner), ETM+ (Enhanced Thematic Mapper), IRS P-6 (Indian Remote Sensing Satellite), LISS IV (Linear Imaging Self-Scanner), and IRS P-5 Cartosat-1 for the assessment of urban area change dynamics between years 1976 and 2008 in Bhagalpur city in the state of Bihar in India. The ground truth and coordinate points were collected using a Global Positioning System (GPS) for the location of the built-up themes prepared in the Geographic Information System (GIS). Land Consumption Rate (LCR) and Land Absorption Coefficient (LAC) were introduced to aid in the quantitative assessment changes. The results show a rapid growth in land consumption rate till 1976, reduction in 1999 and again increase in 2008.

Geospatial strategy for sustainable management of municipal solid waste for growing urban environment

This paper presents the implementation of a Geospatial approach for improving the Municipal Solid Waste (MSW) disposal suitability site assessment in growing urban environment. The increasing trend of population growth and the absolute amounts of waste disposed of worldwide have increased substantially reflecting changes in consumption patterns, consequently worldwide. MSW is now a bigger problem than ever. Despite an increase in alternative techniques for disposing of waste, land-filling remains the primary means. In this context, the pressures and requirements placed on decision makers dealing with land-filling by government and society have increased, as they now have to make decisions taking into considerations environmental safety and economic practicality. The waste disposed by the municipal corporation in the Bhagalpur City (India) is thought to be different from the landfill waste where clearly scientific criterion for locating suitable disposal sites does not seem to exist. The location of disposal sites of Bhagalpur City represents the unconsciousness about the environmental and public health hazards arising from disposing of waste in improper location. Concerning about urban environment and health aspects of people, a good method of waste management and appropriate technologies needed for urban area of Bhagalpur city to improve this trend using Multi Criteria Geographical Information System and Remote Sensing for selection of suitable disposal sites. The purpose of GIS was to perform process to part restricted to highly suitable land followed by using chosen criteria. GIS modeling with overlay operation has been used to find the suitability site for MSW.

Geospatial Strategy for Tropical Forest-Wildlife Reserve Biomass Estimation

This study focus on the biomass estimation of Sariska Wildlife Reserve using forest inventory and geospatial approaches to develop a model based on the statistical correlation between biomass measured at plot level and the associated spectral characteristics. The multistage statistical technique with incorporated the satellite data of IRS P-6 LISS III gives a precise estimation of biomass. Forest cover, forest stratum, and biomass maps were generated in the study. Spectral signatures along with tonal and textural variations were used to classify different forest types validated with GPS and ground truth data. Altitude dependent vegetation and contour information from toposheets were also considered while classifying imagery during interpretation. Sample plots were laid in study area with 0.1 ha area at intersect of the diagonals of the plots. DBH and height of all the trees inside the plot were measured and converted to biomass using volumetric equations depending upon specific gravity. The specific gravity of each tree species differ from each other and sometimes unique in different regions and varies from forest type of different regions. Estimation of tree biomass can serve as useful benchmark for future studies in related areas. Linear equation obtained was used as the model to generate final biomass map where predicted and estimated biomass were compared for each band of the satellite imageries. Linear, logarithm and power exponential models were compared to each other for correlation coefficient. Correlation between estimated and predicted AGB is 0.835 and coefficient of determination (r2) value is 0.698.

Fuzzy AHP for forest fire risk modeling

Purpose – The purpose of study is linked to management and policy‐making strategies, such as forest management, land use planning and sustainable management of natural resources. It aims to help prevent forest fire by taking precautions. It also aims to be helpful for authorities coping during the event of occurrence of fire.Design/methodology/approach – The methodology paradigm applied here is based on knowledge‐based and analytic hierarchy process (AHP) techniques. Knowledge‐based criteria involve topographic and different themes for risk assessment. The assignment of value given to equation is significant due to its importance.Findings – Results are in strong agreement with actual fire occurrences in the past years. The risk zones are identified according to past occurrence of fire. The gradients of low‐ to high‐risk zones are according to fuel, topographic features and weather conditions. Direction and aspect value were taken accordingly.Originality/value – The paper presents forest fire risk zones de...

Attenuation of metal toxicity by frankial siderophores

In order to investigate the role of frankial siderophores in minimizing metal toxicity, Frankia strains were grown at different concentrations of Mg2+, Cu2+, and Zn2+. Growth was observed up to 500 µmol L−1 Mg2+, 10 µmol L−1 Cu2+, and 10 µmol L−1 Zn2+ while the maxima were at 200 µmol L−1 Mg2+, 1 µmol L−1 Cu2+, and 1 µmol L−1 Zn2+. The siderophore production was increased up to 500 µmol L−1 Mg2+, 10 µmol L−1 Cu2+, 100 µmol L−1 (hydroxamate type), and 200 µmol L−1 (catecholate type) Zn2+ while maximum production was found at Mg2+ (200 µmol L−1), Cu2+ (10 µmol L−1), and Zn2+ (10 µmol L−1). The results suggested that the growth was protected at higher concentrations of Mg2+ (up to 500 µmol L−1), Cu2+ (10 µmol L−1), and Zn2+ (10 µmol L−1), possibly due to enhanced siderophore production. Thus, siderophores minimize the metal-induced inhibition of growth in Frankia, likely due to regulation of nutritional imbalances and metabolic processes during adaptation towards metal stress and/or metal toxicity.

Mapping Tree Species in Coastal Portugal Using Statistically Segmented Principal Component Analysis and Other Methods

Hyperspectral sensors record radiances in a large number of wavelengths of the electromagnetic spectrum and can be used to distinguish different tree species based on their characteristic reflectance signatures. Reflectance spectra were measured from airborne hyperspectral AISA Eagle/Hawk imagery in order to identify different Mediterranean tree species at a coastal test site in Portugal. A spectral range from 400 to 2450 nm was recorded at 2-m spatial resolution. The hyperspectral data are divided into five spectral data ranges. The chosen ranges for segmentation are based on statistical properties as well as on their wavelengths, as radiances of a particular wavelength may overlap with neighboring wavelengths. Principal component analysis (PCA) is applied individually to each spectral range. The first three principal components (PCs) of each range are chosen and are fused into a new data segment of reduced dimensionality. The resulting 15 PCs contain 99.42% of the information content of the original hyperspectral image. These PCs were used for a maximum likelihood classification (MLC). Spectral signatures were also analyzed for the hyperspectral data, and were validated with ground data collected in the field by a handheld spectro-radiometer. Different RGB combinations of PC bands of segmented PC image provide distinct feature identification. A comparison with other classification approaches (spectral angle mapper and MLC of the original hyperspectral imagery) shows that the MLC of the segmented PCA achieves the highest accuracy, due to its ability to reduce the Hughes phenomenon.

Geospatial Strategy for Estimation of Soil Organic Carbon in Tropical Wildlife Reserve

This study focuses on the estimation of soil organic carbon of Sariska Wildlife Reserve. The soil organic carbon is one of the most important issues in the research area of the global carbon cycle as it is the largest terrestrial carbon pool. Geospatial and various forest inventory approaches were used during study for statistical correlation between estimated and predicted value. Remote sensing plays a vital role in spatial data acquisition of the ecosystem carbon dynamics at local, regional, and global scale. The advantage of remote sensing is that it provides synoptic observation, periodical and continuous measurement, and availability of digital data for processing standardization. IRS P6 LISS III data (September 2012) were used to analyze the precise estimation of the percentage of the soil organic carbon associated with organic matter in soil. Statistical analysis was performed for finding the regression curve between the predicted and estimated value of soil organic carbon. The results illustrated that the determination of coefficient (r2) between the predicted and estimated SOC values is found to be 0.708.

Remote Estimation of Land Surface Temperature for Different LULC Features of a Moist Deciduous Tropical Forest Region

Potential of Landsat TM thermal sensor is investigated to retrieve land surface temperature (LST) using spectral index (NDVI), spectral radiance and surface emissivity for a moist deciduous tropical forest area of Munger forests (Bihar, India). Surface emissivity values derived from NDVI are directly used for LST estimation. LST varies spatially due to the complexity of land surface cover features and helps in land-use/land-cover profiling. Areas covered with vegetation show minimum temperatures; while barren and exposed land shows high values. Built-up land generally has higher LST, but when dispersed in small pockets in the forests, the LST value decreases as revealed in the results.

Vigorous Appraisal of Fluoride on Industrial Proponent in Thermal Power Plant over Anthropoid Biosphere Using F − Ion-Selective Electrode

This study was conducted to analyze the impact of fluoride in the anthropogenic condition in an industrial region promoting and affecting the health of the workers. Fluoride is toxic to humans in high concentrations, such as can occur in persons working in fluoride-containing mineral industries like aluminum industries. When workers are exposed to fluoride-containing minerals, they can suffer from a variety of health problems, such as dental disease. This paper presents the relationship of different clinical conditions correlated against the fluoride level. Contributing clinical aspects, such as morbidity, dysentery, overcrowding, and skin disease, are also studied to assess the consequences of fluoride upon consistent exposure. The relationship between pH and hardness of water with fluoride was measured, and then spatial maps were generated. The investigations resulted in a conclusion that hardness of water had a more pronounced impact on the level of fluoride concentration as compared with pH. Water with more hardness contains more fluoride concentration (25 mg/ml) as compared with soft water (4 mg/ml). This paper also revealed the concentration of fluoride content in the bodies of aluminum plant workers, which varied from 0.06 to 0.17 mg/L of blood serum in the case of pot room workers and 0.01 to 0.04 mg/L in the case of non-pot room workers. In fingernails, it varied from 0.09 to 3.77 mg/L and 0.39 to 1.15 mg/L in the case of pot room and non-pot room workers, respectively. In urine, it varied from 0.53 to 9.50 mg/L in pot room workers and 0.29 to 1.80 mg/L in non-pot room workers. This paper concluded that water was safe for drinking purposes if it has a low hardness (60-140 mg/ml) and pH (7.1-7.4).

Geospatial Approach to Assess the Impact of Nutrients on Rice Equivalent Yield Using MODIS Sensors’-Based MOD13Q1-NDVI Data

Crop productivity is a major concern all over the world to provide food security, resulting in the green revolution. It is noteworthy that the fertilizer implemented to farmland leads to more desirable cropping patterns. Utilization of agricultural land efficiently for the crop production requires the knowledge of the nutrient inconsistency. This paper has presented the power of geomatics, to retrieve the synoptic and substantial changes in cropping pattern. Results and interpretations lead to the evaluation of the contemporaneous cropping systems. After a major yield parameter scrutiny for crops (rice, wheat, sugarcane, and onion), the magnificent accelerations were suggested. Results demonstrated a correlation r2 value of 0.834 with the estimated crop yield and normalized difference vegetation index. The Rice Equivalent Yield (REY) is highest at the range of 17-21 t/ha in the North, central and southern lower part, lowest at the western part ranging from 7-12 t/ha, with some part with 12-14 t/ha, while the most of the eastern part of the study site has shown the REY values ranging from 14 to 17 t/ha. The surveyed information, such as pH, electical conductivity, and organic carbon of the soil specimen, was used to examine the spatial discrepancies of rice-based cropping systems productivity. Ultimately, the spatialtemporal maps of fertilization pattern, yield parameters (e.g., N, F, and K), and relational REY observation were illustrated using spatial interpolation.