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.     

Generation and study of satellite gravity over Gujarat,India and their possible correlation with earthquake occurrences

High-resolution satellite gravity data have been generated and utilized to infer subsurface geological structures in the area of devastating earthquake that struck the Bhuj region in Gujarat on 26 January 2001. Latitudinal gravity profiles have been generated in the Bhuj, Anjar and IBF regions across the epicentres (23.5° N, 69.8° E/M_w 7.0 in 2001; 23.2° N, 70° E/M_w 7.0 in 1956; 24.2° N, 69.2° E/M_w 7.8 in 1819). Substantial differences in gravity anomaly patterns as high as 37 mGal could be observed existing near the epicentre regions. These gravitational differences might have caused due to the plate tectonic processes and due to the changes in densities of different lithospheric zones/sedimentary layers. Temporal variations of the satellite-derived gravity and their probable relations with already occurred major earthquakes in this region have been studied. Hence we conclude that drastic changes in gravity anomalies can be considered as a precursor for occurrences of substantially large earthquakes.     

Plume and bloom: effect of the Mississippi River diversion on the water quality of Lake Pontchartrain

The opening of the Bonnet Carré spillway to prevent flood threat to New Orleans in April 2008 created a sediment plume in the Lake Pontchartrain. The nutrient rich plume triggered a massive algal bloom in the lake. In this article, we have quantified the spatio-temporal distribution of the plume (suspended solids) and the bloom (chlorophyll-a (chl-a)) in the lake using remotely-sensed data. We processed the Moderate-resolution Imaging Spectroradiometer satellite data for mapping the total suspended solids (TSS) and chl-a concentrations. An existing algorithm was used for estimating TSS whereas a novel slope model was developed to predict the per-pixel chl-a concentration. Both algorithms were successful in capturing the spatio-temporal trend of TSS and chl-a concentrations, respectively. Algal growth was found to be inversely related to TSS concentrations and a time lag of ～45 days existed between the spillway opening and the appearance of the first algal bloom at an observation location.     

Spectral material mapping using hyperspectral imagery: a review of spectral matching and library search methods

Imaging spectroscopy is an emerging and versatile technique that finds applications in diverse fields concerned with remote identification, discrimination and mapping of materials. The large amount of spectral data produced by hyperspectral imaging necessitates the development of automated techniques that convert imagery directly into thematic maps. Spectral library search method, a method of choice for organic compound identification by the mass spectroscopy, has caught the attention of researchers as one of the appropriate methods for an efficient exploitation of high quality spectral data available from the hyperspectral imaging systems. Given the apparent increase in the number of papers appearing on the subject as well as the variety of methods proposed, it is reasonable to say that the field of automated interpretation of reflectance spectral data has passed its infancy now gaining important space in the scientific community. We present an overall view of the literature relevant to the development of library search method, the various search algorithms and systems available in the purview for developing an automated hyperspectral data analysis system for material identification.     

Predicting agricultural drought in eastern Rajasthan of India using NDVI and standardized precipitation index

In the present study, prediction of agricultural drought has been addressed through prediction of agricultural yield using a model based on NDVI-SPI. It has been observed that the meteorological drought index SPI with different timescale is correlated with NDVI at different lag. Also NDVI of current fortnight is correlated with NDVI of previous lags. Based on the correlation coefficients, the Multiple Regression Model was developed to predict NDVI. The NDVI of current fortnight was found highly correlated with SPI of previous fortnight in semi-arid and transitional zones. The correlation between NDVI and crop yield was observed highest in first fortnight of August. The RMSE of predicted yield in drought year was found to be about 17.07 kg/ha which was about 6.02 per cent of average yield. In normal year, it was 24 kg/Ha denoting about 2.1 per cent of average yield.     

A Spatio‐Temporal Graph Model for Marine Dune Dynamics Analysis and Representation

Defining a model for the representation and the analysis of spatio‐temporal dynamics remains an open domain in geographical information sciences. In this article we investigate a spatio‐temporal graph‐based model dedicated to managing and extracting sets of geographical entities related in space and time. The approach is based on spatial and temporal local relations between neighboring entities during consecutive times. The model allows us to extract sets of connected entities distant in time and space over long periods and large spaces. From GIS concepts and qualitative reasoning on space and time, we combine the graph model with a dedicated spatial database. It includes information on geometry and geomorphometric parameters, and on spatial and temporal relations. This allows us to extend classical measurements of spatial parameters, with comparisons of entities linked by complex relations in space and time. As a case study, we show how the model suggests an efficient representation of dunes dynamics on a nautical chart for safe navigation.     

Field Measurements of Plant Emissivity Spectra: An Experimental Study on Remote Sensing of Vegetation in the Thermal Infrared Region

Spectral features of plant species in the visible to SWIR (0.4–2.5 μm) region have been studied extensively, but scanty attention has been given to plant thermal infrared (TIR: 4–14 μm) properties. This paper presents preliminary results of a study that was conducted first time in India to measure radiance and emissivity properties of eight plant species in TIR spectral region in the field conditions using a FTIR (Fourier Transform Infrared) field spectroradiometer working in 4–14 μm at an agriculture experimental farm. Several spectral features in the emissivity spectra of plant species were observed that are probably related to the leaf chemical constituents, such as cellulose and xylan (hemicellulose) and structural aspects of leaf surface like abundance of trichomes and texture. Observations and results from the field measurements were supported by the laboratory measurements like biochemical analysis. These preliminary field emissivity measurements of leaves in TIR show that there is useful spectral information that may be detectable by field-based instrument. More detailed field and laboratory measurements are underway to explore this research theme.     

Towards an integral strategy for modelling uncertain geospatial data

This paper endeavours to put the discussion on errors and uncertainties in geographical information systems (GISs) in a more systematic way by examining the strength and weakness of discrete objects and continous fields, the two distinct schools of spatial data modelling. In doing so, it argues that neither discrete objects nor continous fields alone provide objective and complete representations of highly complex geographical phenomena, though there are good reasons for asserting that continuous fields are better suited to modelling spatial dependence, heterogeneity and fuzzines significant in geographical reality than discrete objects. Thus, there seems to be merit in adopting an integrated model incorporating analytical capabilities of fields and generalization functions of objects, for which extended TIN (triangulated irregular network) models along with their duals (Voronoi diagrams) provide a pragmatical solution.     

Multi‐Season Atmospheric Normalization of NOAA AVHRR Derived NDVI for Crop Yield Modeling

Abstract

A methodology has been developed to normalize the multi‐temporal NDVIs derived from NOAA AVHRR data for the atmospheric effects to the least affected NDVI for development of spectral and spectrometeorological (or spectromet, for short) crop yield models. This is found to reduce the noise in NDVI due to varying atmospheric conditions from season to season and improve the predictability of statistical multiple linear regression yield models. The spectromet yield models for mustard crop in the nine districts of Rajasthan state haven been developed based on normalized NDVIs and have been validated by comparing the predicted yields with the estimated from crop cutting experiments by the state Development of Agriculture.