On radiative forcing of sulphate aerosol produced from ion-promoted nucleation mechanisms in an atmospheric global model

A significant fraction of the total number of particles present in the atmosphere is formed by nucleation in the gas phase. Nucleation and the subsequent growth process influence both number concentration of particles and their size distribution besides chemical and optical properties of atmospheric aerosols. Sulphate aerosol nucleation mechanisms promoted by ions have been evaluated here in a tropospheric interactive chemistry-aerosol module for mass and number concentration in a global atmospheric model. The indirect radiative forcing of sulphate particles is assessed in this model; indirect radiative forcing is different for ion-induced (IIN) and ion-mediated (IMN) mechanisms. The indirect radiative forcing in 10-year simulation runs has been calculated as ?1.42?W/m² (IIN) and ?1.54?W/m² (IMN). The 5% emission of primary sulphate particles in simulations changes the indirect radiative forcing from ?1.42 to ?1.44?W/m² for IIN case, and from ?1.54 to ?1.55 W/m² for the IMN case. More precisely, owing to greater nucleation rates, IMN mechanisms produces greater cooling than the IIN mechanisms in the backdrop that both mechanisms produce almost identical distribution of CDNC in their pre-industrial runs. The inclusion of primary particles in simulations with IIN and IMN mechanisms increases both CDNC and the indirect radiative forcing.     

Influences of local weather, large-scale climatic drivers, and the ca. 11 year solar cycle on lake ice breakup dates; 1905–2004

We investigate the temporal patterns in inter-annual variability in ice breakup dates for Lakes Mendota and Monona, Wisconsin, between 1905 and 2004. We analyze the contributions of long-term trends attributed to climate change, local weather, indices of sunspots, and large-scale climatic drivers, such as the North Atlantic Oscillation (NAO) and El Niňo Southern Ocean Index (ENSO) on time series of lake-ice breakup. The relative importance of the aforementioned explanatory variables was assessed using linear regression and variation partitioning models accounting for cyclic temporal dynamics as represented by Moran Eigenvector Maps (MEM). Model results explain an average of 58 % of the variation in ice breakup dates. A combination of the long-term linear trends, rain and snowfall in the month prior to breakup, air temperature in the winter prior to breakup, cyclic dynamics associated with sunspot numbers, ENSO, and for Lake Mendota, NAO, all significantly influence the timing of ice breakup. Significant cycle lengths were 3.5, 9, 11, and 50 years. Despite their proximity, Lakes Mendota and Monona exhibit differences in how and which explanatory variables were incorporated into the models. Our results indicate that lake ice dynamics are complex in both lakes and multiple interacting processes explain the residuals around the linear warming trends that characterize lake ice records.     

A comparative study of supervised classifiers on a subscene in Junagadh district,Gujarat

This paper describes the results of a comparative study of five classifiers viz., maximum likelihood, modified maximum likelihood, minimum distance to mean. Fisher and min-max, for classifying a subscene of Junagadh district using Landsat Thematic Mapper (TM) data. The kappa coefficient of agreement (k) and per cent correctly classified pixels for training data are used as measures of overall performance. It is observed that maximum likelihood and modified maximum likelihood classifiers perform better than the other three classifiers for this data set. Band combinations (3, 4, S) and (2, 3, 4, S) perform better than the usual combination (1,2,3,4), possibly because of presence of middle infrared band (band 5) on a scene dominated by vegetation cover. The band combination (1, 2, 3, 4, 5, 7) performed the best.     

Temporal change detection in river courses and flood plains in an arid environment through satellite remote sensing

Temporal changes in ephemeral river courses and associated flood plains, which could not be detected by Landsat MSS due to its poor spatial resolution of 80m, have been identified and mapped within 10% accuracy by Landsat TM False colour composite because of its higher spectral and spatial resolution of 30 m. Over a period of 28 years (1958–86) the river courses widened upto 1.8 times through bank erosion due to the recurring flash floods. The flash floods have also caused morphological, soil fertility and landuse changes in the associated flood plains, which could also be monitored by the Landsat TM.     

An integrated approach for ground water investigation in part of Fatehpur Sikri of district agra-a case study

The Fatehpur Sikri area infringing the western UP, Rajasthan border was investigated for its water supply crisis in respect of poor quality and quantity as well. The study has indicated presence of two parallel quartz reefs running in NE-SW direction. Geohydrological and photogeological studies have revealed the possibility of subsurface extension of quartz reefs. However, this weathered area along reefs is promising water bearing zone. Paleo channels are also marked during studies and the area found suitable for ground water exploitation. A map showing various categories is also presented.     

Change detection of linear features in temporally spaced remotely sensed images using edge-based grid analysis

Automatic change detection of land cover features using high-resolution satellite images, is a challenging problem in the field of intelligent remote sensing data interpretation, and is becoming more and more effective for its applications viz. urban planning and monitoring, disaster assessment etc. In the present study, a change in detection approach based on the image morphology that analyses change in the local image grids is proposed. In this approach, edges from both the images are extracted and grid wise comparison is made by probabilistic thresholding and power spectral density analysis for identifying change area. One of the advantages of the proposed methodology is that the temporal images used in the change analysis need not be radiometrically corrected as analysis is based on edge extractions. The grid-based analysis further reduces the error, which might have been introduced by image mis-registration. The proposed methodology is validated by finding the temporal changes in the linear land cover features in parts of Kolkata city, India using three different image data-sets from LISS IV, Cartosat-1 and Google earth having varied spatial resolutions of 5.8 m, 2.5 m and about 1 m, respectively. The overall accuracy in identifying changes is found to be 64.82, 73.86 and 80.93% for LISS IV, Cartosat-1 and Google earth data-set, respectively.     

A Spatial Database of Cropping System and its Characteristics to Aid Climate Change Impact Assessment Studies

Cropping system study is not only useful to understand the overall sustainability of agricultural system, but also it helps in generating many important parameters which are useful in climate change impact assessment. Considering its importance, Space Applications Centre, took up a project for mapping and characterizing major cropping systems of Indo-Gangetic Plains of India. The study area included the five states of Indo-Gangetic Plains (IGP) of India, i.e. Punjab, Haryana, Uttar Pradesh, Bihar and West Bengal. There were two aspects of the study. The first aspect included state and district level cropping system mapping using multi-date remote sensing (IRS-AWiFS and Radarsat ScanSAR) data. The second part was to characterize the cropping system using moderate spatial resolution multi-date remote sensing data (SPOT VGT NDVI) and ground survey. The remote sensing data was used to compute three cropping system performance indices (Multiple Cropping Index, Area Diversity Index and Cultivated Land Utilization Index). Ground survey was conducted using questionnaires filled up by 1,000 farmers selected from 103 villages based on the cropping systems map. Apart from ground survey, soil and water sampling and quality analysis were carried out to understand the effect of different cropping systems and their management practices. The results showed that, rice-wheat was the major cropping system of the IGP, followed by Rice-Fallow-Fallow and Maize-Wheat. Other major cropping systems of IGP included Sugarcane based, Pearl millet-Wheat, Rice-Fallow-Rice, Cotton-Wheat. The ground survey could identify 77 cropping systems, out of which 38 are rice-based systems. Out of these 77 cropping systems, there were 5 single crop systems, occupying 6.5% coverage (of all cropping system area), 56 double crop systems with 72.7% coverage, and 16 triple crop systems with 20.8% coverage. The cropping system performance analysis showed that the crop diversity was found to be highest in Haryana, while the cropping intensity was highest in Punjab state.     

Computerized Database of Salt Affected Soils for Agro‐climatic Regions in the Indo–Gangetic Plain of India Using GIS

Abstract

Indo_Gangetic Plain (IGP) of India that stretched from the foothills of Himalayas near the Punjab State to the Gangetic delta in West Bengal State was known for highly fertile soil and favorable climatic condition for highest production of rice‐wheat. Appearance of soil salinity in large areas of IGP caused a major concern due to loss of productivity. The salt affected soils maps of India (NRSA 1997) showed vast areas of salt affected soils distributed along the Gangetic Plain covering the States of Haryana, Punjab, Uttar Pradesh, Bihar and West Bengal. In the analogue form, these maps contain voluminous data were difficult to handle without messing the whole dataset. An attempt was made to prepare a digitized database of salt affected soils to facilitate easy access, retrieval and map calculations required for reclamation and management of salt affected soil. The salt affected soils maps on 1:250, 000 scale were digitized for the States of Punjab, Haryana, Uttar Pradesh, Bihar and West Bengal using ILWIS. GIS. The Survey of India topomap was used for geo‐referencing and basemap preparation overlaying thematic layers for administrative and political boundaries, infrastructure, irrigation and drainage and settlements. The attribute data on physiography and the soil characteristics were stored in an attribute table and linked with the digitized polygons to prepare a relational database. Combining geo‐referenced (State) maps of Haryana, Punjab, Uttar Pradesh, Bihar and West Bengal using GIS, a composite map for Indo‐Gangetic plain was prepared. Four Agroclimatic regions (ACRs) and seventeen Agroclimatic zones (ACZs) were identified in the Indo‐Gangetic Plain (The Planning Commission of India) for planning and development of natural resources at regional level. The boundaries of ACZs and ACRs were delineated from the primary (master) database of IGP using ILWIS.GIS. The distribution of SAS polygons at regional and zonal level was delineated superimposing digitized boundaries of ACRs and ACZs over the master database of IGP. The state‐wise, region‐wise and zone‐wise extent of SAS was calculated. Soils were essentially saline at Lower‐ and Middle Gangetic Plain regions but highly variable and complex saline‐sodic in the Upper‐ and Trans‐Gangetic Plain regions. The area statistics showed that maximum SAS area occurred in ACR V (Upper Gangetic Plain) in Uttar Pradesh (UP) followed by ACR IV (Middle Gangetic Plain) in UP and Bihar, ACR III (Lower Gangetic Plain) in West Bengal and ACR VI (Trans‐Gangetic Plain) of Haryana and Punjab. Such database in digital format provides geo‐referenced, easy to access and retrievable, relational database comprising of thematic and attribute information of salt affected soils at state, regional and zonal level to facilitate overlay and map calculation of related data such as water quality, climatic, landform etc, useful for planning and decision making in reclamation and management of salt affected soils in IGP and other similar regions.     

Computerized database on salt affected soils in western and central India using GIS

Salt affected soils occupy significant areas in western and central India manifested by the arid and semiarid climate, sandy/clayey soil texture, absence of natural drainage, and inadequate infrastructure and irrigation development. These soils are productive following reclamation and appropriate management. The National Remote Sensing Agency, Hyderabad (India) published state-wise maps of salt affected soils in India on 1:250,000 scale using a legend that includes physiography, soil characteristics, and the aerial extent of the mapping units. In the analogue form, voluminous data contained in such maps were difficult to handle by users of varied backgrounds. An attempt was made to prepare a computerized database of salt affected soils for easy access, retrieval, and manipulation of spatial and attribute data useful for management of salt affected soils. The salt affected soils maps were prepared, for Rajasthan, Gujarat, Madhya Pradesh, and Maharashtra states, overlaying digitized layers of SAS polygons and the Survey of India basemap using the ILWIS (Integrated Land and Water Information System) software. GIS was used to prepare a composite (master) database of western and central India that showed the extent and distribution of salt affected soils. A relational database was prepared combining the digitized polygons with soil characteristics such as nature and degree of salinity (presence of higher concentration of neutral salts and neutral soil reaction), sodicity (presence of higher concentration of basic salts and alkaline reaction) and ground coverage. The regional and zonal databases of salt affected soils were prepared at a suitable scale overlaying agro-climatic regions agro-climatic zones. Spatial relation of salt affected soils with physiography, climate, geology, and agro-eco-sub-regions were evaluated employing map calculations in GIS. Saline soils were prevalent in Gujarat, and Rajasthan while sodic soils were dominant in Maharashtra and Madhya Pradesh. These were distributed primarily in the arid (B) plain of Rajasthan, alluvial (A) and coastal (D) plains of Gujarat, and peninsular plain (F) of Maharashtra and Madhya Pradesh. It occupied 2,596,942 ha (78%) in the western (Rajasthan and Gujarat) and 733,608 ha (22%) in the central (Madhya Pradesh and Maharashtra) regions. The SAS occupied 3.3 million ha in the western and central region constituting 50% of the total salt affected soils in India. The saline and sodic soils occupied 2,069,285 ha (62%) and 1,261,266 ha (38%), respectively.     

Atmospheric correction to IRS-P6 AWiFS data and its validation with ground measurements: A study over the semi-arid region

In this study, we have implemented a fast atmospheric correction algorithm to IRS-P6 advanced wide field sensor (AWiFS) satellite data for retrieving surface reflectance under different atmospheric and surface conditions. The algorithm is based on MODIS climatology products and simplified use of Second Simulation of Satellite Signal in Solar Spectrum (6S) radiative transfer code. The algorithm requires information on aerosol optical depth (AOD) for correcting the satellite dataset. The atmospheric correction algorithm has been tested for IRS-P6 AWiFS False colour composites covering the International Crops Research Institute for the Semi-Arid Tropics Farm, Patancheru, Hyderabad, India, under varying atmospheric conditions. Ground measurements of surface reflectance representing different land use/land cover, i.e. red soil, chick pea, groundnut and pigeon pea crops were conducted to validate the algorithm. Terra MODIS AOD₅₅₀ validated with Microtops-II sun photometer–derived AOD₅₀₀ over the urban region of Hyderabad exhibited very good correlation of ～0.92, suggesting possible use of satellite-derived AOD for atmospheric correction.