Watershed Delineation in Flat Terrain of Thar Desert Region in North West India – A Semi Automated Approach Using DEM

Thar desert spreads in western part of Rajasthan, northern part of Gujarat, and some parts of Punjab and Haryana. The terrain is dominated by slightly sloping plains, broken by some dunes and low barren hills. The area is characterized by low average annual rainfall which is erratic in distribution and intensity. Drought will remain a major hindrance for agricultural production in Thar desert. Due to water stress condition, many watershed based development activities has been adopted by government and non-government organizations for the growth and sustainable development of this region. The need of this hour is preparation of a national level watershed atlas of 1:50,000 scale because majority of thematic maps are being produced presently on same or 1:10,000 scale. The manual delineation of watershed boundary in flat terrain based on topographic map will be time consuming and less accurate in the absence of prominent contour lines. Automated approach for watershed delineation using Digital Elevation Model (DEM) along a suitable algorithm has the advantage because the output is not only less time consuming but also independent from human decisions. Hence, a case study has been carried out in Churu sub-basin part of Indus basin which is located in Thar desert region. Depression less DEM with different spatial resolutions was used as input in hydrology tool of ArcGIS spatial analyst function for characterization of watersheds. The Churu sub-basin has been divided into various numbers of watersheds with an average size of 600 km². These watershed boundaries have been validated with respect to high resolution satellite imageries (IRS P6 LISS IV), Survey of India toposheets, ancillary data and limited field checks.     

Shoreline Change Analysis along the Coast of South Gujarat,India, Using Digital Shoreline Analysis System

Shoreline changes along the south Gujarat coast has been analyzed by using USGS Digital Shoreline Analysis System (DSAS) version 4.3. Multi-temporal satellite images pertaining to 1972, 1990, 2001 and 2011 were used to extract the shoreline. The High water line (HTL) is considered as shoreline and visual interpretation of satellite imageries has been carried out to demarcate the HTL based on various geomorphology and land use & land cover features. The present study used the Linear Regression Method (LRR) to calculate shoreline change rate. Based on the rate of shoreline changes, the coastal stretches of study area has been classified in to high erosion, low erosion, stable, low accretion and high accretion coast. The study found that about 69.31 % of the South Gujarat coast is eroding, about 18.40 % of coast is stable and remaining 12.28 % of the coast is accreting in nature. Field investigation was carried out which confirmed the coastal erosion/accretion derived from the analysis. The high erosion area are mostly found along the Umergaon (near Fansa, Maroli, Nargol, Varili river mouth, Umergaon light house) and Pardi (Kolak, Udwara)Taluka in Valsad district. Stable coastal length of the study area is 21.59 km and mostly found in Nani Dandi and near Onjal. High accretion (3.70 %) was only found near Hajira and low accretion (8.58 %) are distributed the study area. The main causes of coastal erosion of the study area were the strong tidal currents accompanied by wave action and reduced the sediment load of the river.     

Generation of Vegetation Fraction and Surface Albedo Products Over India from Ocean Colour Monitor (OCM) Data Onboard Oceansat-2

The use of Local Area Coverage (LAC) data from Ocean Color Monitor (OCM) sensor of Oceansat-2 with its high radiometric resolution (12 bits/pixel) and 2-day repeat cycle for rapid monitoring of vegetation growth and estimating surface albedo for the Indian region is demonstrated in this study. For the vegetation monitoring, normalized difference vegetation index (NDVI) and vegetation fraction (VF) products were estimated by maximum value composite approach fortnightly and were resampled to 1 km. The surface albedo products were realized by converting narrow-band eight-band spectral reflectance OCM data to a) visible (300–700 nm) and b) broad band (300–3,000 nm) data. For validation, the derived products were compared with respective MODIS global products and found to be in good agreement.     

Automated approaches for displaying spatially oriented time‐series data through image processing techniques

This study demonstrated the cartographic implications of automated image processing and computer graphics for the study of time‐series data. Automated statistical and image processing techniques were applied to a case study data set consisting of weekly Crop Moisture Index (CMI) values summarized at 174 state cooperative weather stations within Oklahoma for the time period between February and October, 1980. Computer generated isoline maps of the CMI values were interpolated and rescaled into a series of 32 grid matrices for input into a raster‐based ERDAS image processing software system. Principal Components Analysis (PCA) was used to develop graphic models that synthesized the multi‐temporal data into statistical dimensions that represented the most significant elements of CMI variability. Graphic models of the PCA statistical vectors were displayed individually, in conjunction with eigenvector loadings, and as composite images. Resultant images were analyzed statistically and graphically through the generated CMI grid matrices to ascertain the location, severity, and progression of drought represented in the CMI values. Traditional image processing techniques and devices were combined with the ERDAS software system to transform the multi‐temporal CMI data into multi‐dimensional images that represented the drought's spatial and temporal signature unobscured by redundant information.     

Monitoring of salt affected soils — A case study using aerial photographs,salyut‐7 space photographs,and landsat TM data

Soils of part of Ukai‐kakarapar Command area, Gujarat (India) have been mapped at 1:25, 000 scale using aerial photographs of December 1977. It was observed that about 36.3% of the area was affected by soil salinity/alkalinity. The test area has been remapped using Salyut‐7 space photographs taken during Indo‐Soviet joint flight in April, 1984. The area affected by soil salinity/alkalinity was found to be substantially higher (80.3%). The earlier mapping using aerial photographs was done when the soil surface was compartively moist (December 1977) as compared to date of Salyut‐7 photography (April 1984), when the soil surface was likely to be devoid of moisture and the salts moved to the surface. To have easy comparision with the map prepared by using aerial photographs, Landsat TM data of December, 1985 was used in which 45.7% of the total area was mapped as salt affected. The extent of area delineated using Landsat TM was higher than that of 1977 but much lesser than the area delineated using Salyut‐7 (MKF‐6M) photographs. This indicated that the increase in the extent of salt affected area in the map prepared using the MKF‐6M photographs might be partly due to actual increase in the salinity/alkalinity and partly due to the seasonal affects. Among the various bands of MKF‐6M, band ‐4 was found to be the best for delineating the salt affected soils. The boundaries were sharper in the FCC and band No.4 of MKF‐6M than in the aerial photographs.     

Earth observations during space shuttle flight STS‐41: Discovery's mission to planet earth

Abstract

Multi‐temporal ERS‐1 SAR data acquired over a large agricultural region in West Bengal was used to classify kharif crops like rice, jute and sugarcane. Rice crop grown under lowland management practice showed a temporal characteristic. The dynamic range of backscatter was highest for this crop in temporal SAR data. This was used to classify rice using temporal SAR data. Such temporal character was not observed for the other study crops, which may be due to the difference in cultivation practice and crop calendar. Significant increase in backscatter from the ploughed fields was used to derive information on onset and duration of land preparations. Synergistic use of optical remote sensing data and SAR data increased the separability of rice crop from homesteads and permanent vegetation classes.     

NEW METHODS OF COMPILING GENERAL REFERENCE MAPS IN ATLAS CARTOGRAPHY

Measures to improve the effectiveness and informational content of general reference maps and other materials in atlases designed for the general public are outlined. Emphasis is placed upon (a) enhancing the readability and visual appeal of color “landscape” maps, providing a generalized, small-scale aerial view of the region(s) of interest–this through the application of principles of perception and colorimetry–and (b) developing larger-scale “reference” maps maximizing levels of graphic detail without jeopardizing ease of perception–this based on a careful study of general reference maps in atlases worldwide and broadly based testing of users with various levels of map reading skills. Translated from: Izvestiya vysshykh uchebnykh zavedeniy: Geodeziya i aerofotos'yemka, 1985, No. 6, pp. 111-115.     

Multi‐temporal Mapping of Burned Forest over Canada Using Satellite‐based Change Metrics

Abstract

A procedure for continental‐scale mapping of burned boreal forest at 10‐day intervals was developed for application to coarse resolution satellite imagery. The basis of the technique is a multiple logistic regression model parameterized using 1998 SPOT‐4 VEGETATION clear‐sky composites and training sites selected across Canada. Predictor features consisted of multi‐temporal change metrics based on reflectance and two vegetation indices, which were normalized to the trajectory of background vegetation to account for phenological variation. Spatial‐contextual tests applied to the logistic model output were developed to remove noise and increase the sensitivity of detection. The procedure was applied over Canada for the 1998‐2000 fire seasons and validated using fire surveys and burned area statistics from forest fire management agencies. The area of falsely mapped burns was found to be small (3.5% commission error over Canada), and most burns larger than 10 km2 were accurately detected and mapped (R² = 0.90, P<0.005, n = 91 for burns in two provinces). Canada‐wide satellite burned area was similar, but consistently smaller by comparison to statistics compiled by the Canadian Interagency Forest Fire Centre (by 17% in 1998, 16% in 1999, and 3% in 2000).     

A Place to Howl: A GIS Instructional Module on the Mexican Gray Wolf

Abstract

This paper covers the development of a GIS instructional module centered on the reintroduction of the Mexican Gray Wolf in the Southwest, United States. This module is used in an undergraduate geography course on the United States. The paper also reports on how forty‐one students applied the module in trying to find an appropriate location to reintroduce the wolf.     

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.