Forest stand biomass serves as an effective indicator for monitoring REDD (reducing emissions from deforestation and forest degradation). Optical remote sensing data have been widely used to derive forest biophysical parameters inspite of their poor sensitivity towards the forest properties. Microwave remote sensing provides a better alternative owing to its inherent ability to penetrate the forest vegetation. This study aims at developing optimal regression models for retrieving forest above-ground bole biomass (AGBB) utilising optical data from Landsat TM and microwave data from L-band of ALOS PALSAR data over Indian subcontinental tropical deciduous mixed forests located in Munger (Bihar, India). Spatial biomass models were developed. The results using Landsat TM showed poor correlation (R2 = 0.295 and RMSE = 35 t/ha) when compared to HH polarized L-band SAR (R2 = 0.868 and RMSE = 16.06 t/ha). However, the prediction model performed even better when both the optical and SAR were used simultaneously (R2 = 0.892 and RMSE = 14.08 t/ha). The addition of TM metrics has positively contributed in improving PALSAR estimates of forest biomass. Hence, the study recommends the combined use of both optical and SAR sensors for better assessment of stand biomass with significant contribution towards operational forestry. 相似文献
AbstractThis research deals with the surface dynamics and key factors – hydrological regime, sediment load, and erodibility of floodplain facies – of frequent channel shifting, intensive meandering, and lateral instability of the Bhagirathi River in the western part of the Ganga-Brahmaputra Delta (GBD). At present, the floodplain of the Bhagirathi is categorized as a medium energy (specific stream power of 10–300 W m?2), non-cohesive floodplain, which exhibits a mixed-load and a meandering channel, an entrenchment ratio >2.2, width–depth ratio >12, sinuosity >1.4, and channel slope <0.02. In the study area, since 1975, four meander cutoffs have been shaped at an average rate of one in every 9–10 years. In the active meander belt and sand-silt dominated floodplains of GBD, frequent shifting of the channel and meander migration escalate severe bank erosion (e.g. 2.5 × 106 m3 of land lost between 1999 and 2004) throughout the year. Remote sensing based spatio-temporal analysis and stratigraphic analysis reveal that the impact of the Farakka barrage, completed in 1975, is not the sole factor of downstream channel oscillation; rather, hydrogeomorphic instability induced by the Ajay–Mayurakshi fluvial system and the erodibility of floodplain sediments control the channel dynamics of the study area. 相似文献
The objective of the study is to investigate spatio-temporal variations of PM10, PM2.5, and PM1 concentrations at seven residential sites, located in the vicinity of opencast coal projects, Basundhara Garjanbahal Area (BGA), India. Meteorological parameters such as wind speed, wind direction, relative humidity, and temperature were collected simultaneously with PM concentrations. Mean concentrations of PM10 in the range 215 ± 169–526 ± 412 μg m?3, PM2.5 in the range of 91 ± 79–297 ± 107 μg m?3, PM1 in the range of 68 ± 60–247 ± 84 μg m?3 were obtained. Coarse fractions (PM2.5–10) varied from 27 to 58% whereas fine fractions (PM1–2.5 and PM1) varied in the range of 51–73%. PM2.5 concentration was 41–74% of PM10 concentration, PM1 concentration was 31–62% of PM10 concentration, and PM1 concentration was 73–83% of PM2.5 concentration. Role of meteorology on PM concentrations was assessed using correlation analysis. Linear relationships were established among PM concentrations using least square regression analysis. With the aid of principal component analysis, two components were drawn out of eight variables, which represent more than 75% of variance. The results indicated that major sources of air pollutants (PM10, PM2.5, PM1, CO, CO2) at the residential sites are road dust raised by vehicular movement, spillage of coal generated during transportation, spontaneous combustion of coal, and biomass burning in village area. 相似文献
An examination of river channels has ability to provide substantial information regarding the geomorphic characteristics, control of lithology, tectonic uplift and geomorphic evolution during the geological past of an area. In this paper, a detailed study of geomorphic and structural investigation has been carried out for Pravara basin, Maharashtra, with the help of 90-m resolution SRTM DEM and geospatial techniques. Drainage network analysis performed in this paper demonstrates the general geomorphic characteristics, while the analysis of longitudinal profile synthesises lithological control over Pravara basin. Pravara is a 6th order drainage basin, encompassing an area of 2637 km2. Bifurcation ratio reveals low to moderate structural control. Due to the hard rock lithology, the drainage density and stream frequency are low, and it indicates higher permeability in the sub-surface layers. The shape parameters denote that Pravara is highly elongated and it is easier to control floods in this basin. Relief parameters show very steep slope and higher vulnerability to the slope failure in some areas. Upstream of Pravara river has shown that series of breaks and knickzones indicate active erosion and acute lithological control on the channel. Major breaks are observed only in the main channel whereas in two major tributaries, no such breaks found, instead these tributaries are characterised by several knickzones which indicate regional variation in the lithological physiognomies. Different lithological stages on knickpoint and channel incision substantiate rejuvenation of Pravara river in several phases during geological past. The geospatial methodology carried out in this study can be pragmatic elsewhere around this world to recognise the geomorphic appearances and lithological control of a drainage basin. 相似文献
Palaeobiogeographical distribution of gastropod genera from the Paleocene and the Eocene has been analysed. Based on this distribution, formal palaeobiogeographical provinces have been established and their relationships are sought. It has been found that the provinces were largely restricted to the palaeo-tropics and subtropics mainly of the northern hemisphere and they share a large proportion of their generic composition. The Northern Tropical Realm has been established to include these provinces. The distribution evinces presence of ocean surface currents in the tropics across longitudes. The possible currents moved through the relict Tethys Ocean, across the Atlantic Ocean and perhaps also across the Pacific. However, planktotrophic larvae of these benthic molluscs could not cross the deep ocean barrier that lay between the Northern Tropical Realm and the Austro-New Zealand Province of the southern hemisphere. The gastropod fauna in the latter province evolved independently. Distribution of all the provinces within palaeo-tropics and subtropics indicates strong control of temperature over it. Paleocene–Eocene Thermal Maximum appears to be responsible for extinction and range contraction of high latitude faunas. Low latitude faunas also suffered significant extinction. However, large diversification in the Eocene was a response to widespread transgression that coincided with the thermal event. 相似文献
Accurate prediction of settlement for shallow footings on cohesionless soil is a complex geotechnical problem due to large uncertainties associated with soil. Prediction of the settlement of shallow footings on cohesionless soil is based on in situ tests as it is difficult to find out the properties of soil in the laboratory and standard penetration test (SPT) is the most often used in situ test. In data driven modelling, it is very difficult to choose the optimal input parameters, which will govern the model efficiency along with a better generalization. Feature subset selection involves minimization of both prediction error and the number of features, which are in general mutual conflicting objectives. In this study, a multi-objective optimization technique is used, where a non-dominated sorting genetic algorithm (NSGA II) is combined with a learning algorithm (neural network) to develop a prediction model based on SPT data based on the Pareto optimal front. Pareto optimal front gives the user freedom to choose a model in terms of accuracy and model complexity. It is also shown how NSGA II can be effectively applied to select the optimal parameters and besides minimizing the error rate. The developed model is compared with existing models in terms of different statistical criteria and found to be more efficient. 相似文献
The study assesses the level of development and disparities in terms of living conditions of the households in the districts of Bundelkhand region. To measure actual scenario of living conditions of the HHs, a Composite Index was developed on the basis of 18 indicators. Even to assess living conditions of the HHs, four indices have been developed namely Housing Index, Physical Capital Index and Asset Index. The level of development of the districts has been categorized on the basis of Composite Index value. The results show that there is a wide disparity in terms of conditions of living in different districts of Bundelkhand region. The results also shows that northern part of Bundelkhand region is more developed as compared to southern part. From the result, it was recorded that the districts belonging in Madhya Pradesh having better condition of living in comparison to Uttar Pradesh in Bundelkhand region. The research study suggests that authorities should focus on the proper implementation of the existing policies and more effective planning and policies should be implemented to enhance the better living conditions of the households in Bundelkhand region.