Utilization of remotely sensed data for soil resource mapping and its interpretation for landuse planning of Bhiwani district,Haryana

Visual interpretation of IRS-1A LISS-II (October 1988 & Feb. 1989) FCC (spectral bands 2, 3 & 4) at 1:50,000 scale was carried out for soil resource mapping of Bhiwani district (Haryana State) covering on area of 5099 sq. kim. Based on image characteristics, element analysis (landform, vegetation & erosion) and field traverses, physiography-soil relationship was established. Major physiographic units identified in the area are: Aeolian plain, Fluvio-acolian plain, Transitional plain, Alluvial plain, Hills and Pediments. Area was divided into 34 subunits. Final physiography-soil map on 1:50,000 scale was prepared. Taxonomically, the soils of each unit were classified and are found as: In aeolian plain—Typic Torripsamments/coarse loamy, Typic Camborthios; Fluvio-aeolian plain-Aridic Ustipsamments/coarse loamy/fine loamy Typic/Udic Ustochrepts; Alluvial plain—Typic Ustipsamments/coarse loamy/fine loamy Typic/Udic Ustochrepts; Hills and Pediments—fregmental Lithic Torriorthents/Typic Torripsamments. Interpretation for each subunit was made regarding land suitability for various land utilisation types. It was found that hills and pediments, dunal ridges, dunal complexes and serub-lands are best suitable for forestry and horiculture plantations. Dunal plains and inter-dunal depressions are best suitable for gram/bajra/oilseeds/guar, very gently sloping dunal plain and low lying plain are suitable for wheat/arhar/cotton/sunflower.     

Assessment and monitoring of estuarine mangrove forests of Goa using satellite remote sensing

The present study highlights the application of satellite remote sensing in the assessment and monitoring of the mangrove forests along the coastline in Goa state of India. Based on onscreen visual interpretation techniques various land use and land cover classes have been mapped and classified. An attempt has been made to analyse changes in the mangrove forest cover from 1994 to 2001 using IRS-1B LISS-II and IRS-1D LISS-III data. An increase in the mangrove vegetation in the important estuaries has been found during 1994 and 2001. During this period, the mangrove forest increased by 44.90 per cent as a result of increased protection and consequent regeneration. Plantation of mangrove species has been raised in 876 ha (1985 to 1997) by the State Forest Department¨     

Evaluation of multisensor data for delineating salt affected soils in arid rajasthan

The Landsat (MSS and TM), SPOT (PLA and MLA) and IRS (LISS-I and LISS-II) images of crop free period (April, May), rainfed crop (October) and rabi irrigated crop (January, February) have been evaluated for their capabilities of mapping (1) primary salt affected soils: (slightly, moderately and severely) (2) saline water irrigated saline soils, (3) sodic water irrigated sodic soils and (4) salt affected soils due to tank seepage in the arid region of Rajasthan. The moderately and severe salt affected soils could be mapped with Landsat, (IRS LISS-I) and SPOT, images of any season. However, the summer season imagery provided maximum extent of salt affected soils. The LISS-II imagery also provided delineation of slightly salt affected soils in addition to the moderate and severely salt affected soils. The delineation of saline and sodic water irrigated areas was possible by using Landsat False Colour Composite for the January month by their characteristic reflectance, existing cropping pattern and the quality of irrigation water being used in the area. The IRS (LISS-II) and SPOT PLA images for the May month were also used for mapping of saline and sodic water irrigated soils.     

Land productivity assessment and mapping through integration of satellite and terrain slope data

Evaluation and mapping of spatial variations of land productivity is very important for effective landuse planning. The present study was undertaken in watershed of the Song river (Dehra Dun district, U.P.), for assessing and mapping land productivity using modified Storie Index following integrated approach. This approach utilizes soilscape information (derived from digital IRS-IA LISS-II data), soil characteristics (field observed and laboratory analysed) and terrain slope information (obtained from Survey of India topographical maps). The approach consists of preparation of Storie Index productivity rating factors such as: A (soil profile character), B (soil texture), X (soil physical and fertility conditions), and C (land slope), and computerised integration of these maps to generate land productivity map. The results indicate that in the watershed 30.6%, 19.6%, 12.2%, 11.8% and 18.8% areas have been found to be under good, fair, poor, very poor and not suitable, land productivity classes, respectively.     

Accuracy assessment in cotton acreage estimation using Indian remote sensing satellite data

The accuracy of cotton crop classification using satellite data has been assessed with respect to a detailed land cover map prepared by field survey. The effect of spatial resolution on classification accuracy was studied using LISS-I (spatial resolution 72.6 m) and LISS-II data (spatial resolution 36.25 m) of the Indian remote sensing satellite IRS-1B. The performances of the maximum likelihood and the minimum distance to mean as classifiers have also been assessed. LISS-II data have been found to give a higher classification accuracy. The estimate of cotton acreage using LISS-II data was closer to that obtained from the base map. The maximum likelihood classifier (MXL) and the minimum distance to mean (MDM) classifier performed equally well.     

Landuse/land cover mapping and change detection using satellite data — a case study of dehlon block, district Ludhiana, Punjab

The land use information collected for Dehlon block of Ludhiana district, Punjab from the analysis of the IRS-1B LISS-II data for the year 1993 and IRS PAN data for the year 1997 and SOI topographical maps for 1964 revealed a large change in the area of different land use categories during the period from 1964 to 1997. The agricultural land covering an area of about 94.14 per cent in 1964 reduced to 90.26 per cent in 1997. while the area under rural settlements increased from 312 ha in 1964 to 1162 ha in 1997. An extra area of about 169 ha under waste land was added during the period under study making total waste land area to about 400 ha in 1997. However, the block lacks the forest cover of the required limit. Considerable change in living environment was observed in the block. Number of persons per unit settlement area (ha) being 213.3 in 1964 reduced to 97.1 in 1991; it indicate that the living standard of the people of the block has improved with the changed cropping pattern and increased agricultural production during the period from 1964 to 1991.     

Environmental aspects in Dalli-Rajhara iron ore mine area,M.P. using digital image processing techniques

Landsat MSS (1982) and IRS LISS-II (1989) data have been used to study the land use/land cover changes in Dalli-Rajhara iron ore mine area. Supervised classification has been performed on the temporal data to generate land use/land cover maps. Land use/land cover categories generated from IRS LISS-II data of 36 m resolution has been resampled to 80 m and areal statistics have been computed for 2, 4, 8 and 10 km wide strips around Dalli-Rajhara iron ore mine. The environmental impact due to on-going mining activities in the area has been analysed. The results of this study indicate that due to increase in mine-related and agricultural activities, forests have been degraded and also forest areas have been reduced considerably.     

A comparative evaluation of IRS-1A LISS-II and landsat MSS images using computer-aided lineament data analysis

Lineament patterns detected from remotely sensed data provide useful information to geoscientists, specially in the study of basement tectonics, groundwater targetting and mineral exploration. Improvements in the spatial resolution of satellite images have resulted in the detection of short and faint lineaments which have hitherto gone unnoticed The IRS-1A LISS-II data offers a significant improvement in spatial resolution as compared to the Landsat MSS. A set of computer programmes developed for analysis of lineaments were used to study the parameters such as lineament frequency, length and density in order to quantify the added information derived using IRS-1A LISS-II images. The incremental contribution of LISS-II images are of the order of 100 per cent for lineament frequency and about 60 per cent for total line kilometers of lineaments detected.     

Sustainable development of land and water resources using geographic information system and remote sensing

Realizing the potential of spaceborne multispectral measurements in providing spatial information on natural resources, and of Geographic Information System (GIS) in integrating such information with the socio-economic data and other collateral information to arrive at derivative information, we report here the results of a study which was taken up in a watershed in Charkhari block of Mahoba district, northern India, to generate the information on natural resources from Indian Remote Sensing Satellite (IRS-1B) Linear Imaging Self-scanning Sensor (LISS-II) images through a systematic visual interpretation, and its subsequent integration with the collateral information in a GIS environment to develop optimal land use plan/action plan for sustainable development of its land resources. Since permanent vegetation cover in the watershed has been dwindling due to population pressure, the need for establishing more vegetation cover has been stressed.     

Delineation of social forestry plantations under various afforestation programmes using satellite digital data

Digital analysis of IRS 1A LISS-II (23-03-1991) data was used to delineate social forestry plantations in Matar taluka of Kheda district, Gujarat. VAX 11/780 image processing system was used to categorise the various plantations using supervised maximum likelihood classification. The classified output yielded three categories of plantations viz.,Eucalyptus spp.,Acacia spp., and mixed spp. The statistics for all the categories were also generated.     

Utility of satellite data for land evaluation in land use planning for a part of Northern Karnataka

The study reported herein deals with the utility of satellite remote sensing techniques for land evaluation for agricultural land use planning. False colour composite of Landsat imagery in the scale of 1:250,000 was visually interpreted for physiography that formed the base for mapping soil and land resources in the field. The small-scale soil map thus prepared has thirteen map units with association of soil families. Soil and land resource units shown on these small-scale maps were evaluated for their suitability for growing sorghum crop by matching the relevant land qualities against the land requirements for sorghum. The land evaluation carried out for growing sorghum crop in the study area revealed that about 38.6 per cent is highly suitable (S1), 31.5 per cent moderately suitable (S2) and 24.5 per cent marginally suitable (S3). An area of about 5.4 per cent is not suitable, of which 3.0 per cent is currently not suitable (N1) and 2.4 per cent permanently not suitable for growing sorghum crop.     

Application of GIS for land-use/land-cover change analysis in a mountainous terrain

Integration of remote sensing data with other spatial/non-spatial data was carried out using ARC/INFO software package. A simple classification technique was adopted for land cover/land-use change analyses in relation to elevation, slope, aspect and bio-climatic classes. Suitability assessment of land where agricultural extension occurred between 1963 and 1993 was made using GIS software package. Expansion of agriculture and was found to be maximum in 2200-2400 m elevation zone and 20–30° slope classes. When topographic aspects were considered expansion was maximum on south east and west facing slopes. The loss of vegetal cover is estimated to be 15 per cent between 1963–1993. However regeneration of forest was found to be maximum in elevation ranges of 1600–2000 metre and mostly having 20–30° average slope, Land deterioration over the two mapping periods was identified and strategies were suggested to mitigate the problem.     

Application of Remote Sensing for Environmental Monitoring in Bijolia Mining Area of Rajasthan

Impact of raining Vindhyan Sandstone, at 3D centres spread over 617 sq kms, by Open cast method in Bijolia area, Rajasthan on the environment, both trataral and social, assessed ever a period of 20 years (1971-91), revealed that it had affected nearly 20 times the area of lease. The study was earried out using Multidate remote sensing date for 1984 and 1991 and topographical maps of 1971, for change detection in land use pattern with the increase in mining activity. Whereas area covered fey mining activity increased by 35.3 times in 20 years, the forest cover decreased by 46.3 per cent The dense forest decreased by 90 per cent and the land under agriculture decreased by 12 per cent Consequently the waste land increased by 67.4 per cent. Hydrologtcal regime was affected by way of blocking the channels and lowering of water table. Solid particulate matter (SPM) values in mining centres were found to be more than double the normal, leading to diseases related to tungs and liver such as Silieosis. Bronchitis, Asthama and T.B. Nearly 25 per cent of workers were found to suffer from one or the other disease. 50 per cent of mine workers suffer from malaria as a consequence of breeding mosquitoes in stagnant waters m mine pits and labour colonies Noise levels at the active zones like drilling, blasting and mine service stations range from 96 to 125 dB as against the permissible limit of 75 dB affecting health and mental facility of mine workers.     

Land degradation mapping in the upper catchment of river Tons

A study on land degradation in the upper catchment of river Tons, a tributary of Yamuna river, in Uttarkashi district of the Uttarakhand state, was carried out using on-screen visual interpretation of IRS LISS-III + PAN merged data. The study area, which is largely mountainous, includes Govind Wildlife Sanctuary and National Park. Vegetation cover, slope and erosion status were used as criteria for the delineation of four major land degradation categories viz., undegraded, moderately degraded, degraded and severely degraded. More than 50 per cent of the study area is reported to be covered with snow and grassland. The moderate to severely degraded area worked out to be 42.4 per cent of the total area. The 32.8 per cent of area was found to be moderately degraded, followed by degraded (6.63%) and severely degraded (2.88%) areas. The depletion of vegetation cover on mountainous terrain and subsequent cultivation without proper protection measures is the reason for severe soil erosion and land degradation. In view of the existing land degradation situation, the catchment requires immediate treatment on priority for the sustenance of agriculture and wild life. It is expected that these measures will reduce the silt load in the river Tons and eventually, in river Yamuna.     

Patterns of carbon sequestration in forests of western ghats and study of applicability of remote sensing in generating carbon credits through afforestation/reforestation

Satellite remote sensing is a proven tool for mapping landuse patterns and estimating vegetation biomass/carbon. Present study aims at estimating the potential of forests of Radhanagari WLS (Western Ghats, India) to sequester the atmospheric carbon-di-oxide, using ground based observations coupled with satellite remote sensing. The study area was stratified for dominant forest types based on the structure and composition of vegetation and elevation variations. Permanent sample plots were laid down in these homogeneous vegetation strata (HVS) to make different observations during time 1 and time 2. Carbon sequestration by plantations was also studied and compared with natural forests. Species and area-specific biomass equations were used for estimating carbon pool and sequestration. Among natural forests ‘mixed moist deciduous’ forests exhibited highest sequestration rate (8%), whereas, plantation as obvious had a comparatively higher sequestration rate than natural forests (20.27%). Total carbon sequestration by forests of the Radhanagari WLS between 2004 and 2006 is 78742.09 tons. Eligible land for reforestation activity under clean development mechanism (CDM) of Kyoto Protocol was identified using satellite remote sensing using 1989 and 2005 datasets and it was observed that the potential land that can be used for reforestation activity is 10080 ha.     

Towards automated 10–30 m resolution land cover mapping in insular South-East Asia

In this study, we create and critically analyse an automated decision tree classification approach for regional level land cover mapping in insular South-East Asian conditions, using a combination of 10–30 m resolution optical and radar data. The resulting map contains 11 land cover classes and reveals a great deal of contextual information due to high spatial resolution. A limited accuracy assessment indicates 59–97% class wise accuracies. The unprecedented spatial detail of closed canopy oil palm mapping (with user’s accuracy of 90%) is seen as the most promising feature of the mapping approach. The incapability of separating primary forests from other tree cover, and the large variety of different landscapes (e.g. home gardens and tea plantations) classified as shrubland, are considered the main areas for future improvement. Overall, the study demonstrates the great potential of multi-source 10–30 m resolution high data volume land cover mapping approaches in insular South-East Asian conditions.     

Spectral angle mapper and object-based classification combined with hyperspectral remote sensing imagery for obtaining land use/cover mapping in a Mediterranean region

In this study, we test the potential of two different classification algorithms, namely the spectral angle mapper (SAM) and object-based classifier for mapping the land use/cover characteristics using a Hyperion imagery. We chose a study region that represents a typical Mediterranean setting in terms of landscape structure, composition and heterogeneous land cover classes. Accuracy assessment of the land cover classes was performed based on the error matrix statistics. Validation points were derived from visual interpretation of multispectral high resolution QuickBird-2 satellite imagery. Results from both the classifiers yielded more than 70% classification accuracy. However, the object-based classification clearly outperformed the SAM by 7.91% overall accuracy (OA) and a relatively high kappa coefficient. Similar results were observed in the classification of the individual classes. Our results highlight the potential of hyperspectral remote sensing data as well as object-based classification approach for mapping heterogeneous land use/cover in a typical Mediterranean setting.     

Accuracy of mustard and wheat inventory at village-level using liss-II digital data in pali district, Rajasthan

A study was carried out to estimate the accuracy of crop discrimination and area inventory for wheat and mustard using IRS LISS-II digital data of two acquisition dates D1 (Dec. 28, 1994) and D2 (Feb. 10, 1995) over a test site (1413 ha) comprising of two villages in Pali district, Rajasthan, The D1 and D2 were optimal acquisitions for mustard and wheat respectively with deviations in aereage estimates of less than five per cent in comparison to field survey. The percent correctly classified pixels ter training site for optimal dates of each crop ranged between 85 and 86 per cent and they were much lower for other dates. These results with lower accuracies than reported earlier for sites with single dominant crop are indicative of accuracies for discrimination and area inventory fot sites having two crops and also sensitivity to acquisition period.     

Inventory of degraded lands of Palamau district, Bihar — A remote sensing approach

In this study, an attempt has keen made for the identification, categorisation and mapping of degraded lands in Palamau district of Bihar using remotely sensed data (IRS-1A, raise colour composite, on 1:50,000 scale), It was observed that water erosion is the main cause of land degradation affecting 6.27 per cent area of the district, of which 5.22 per cent is subjected to severe to very severe erosion and remaining 1.05 per cent is moderately to severely gulleid land Degradation due to rock quarries, mine spoils and dumps accounted for only 0.01 per cent of the district area. Degraded lands were mostly confined to agricultural areas (4.76%) follwed by forest lands (1.10%) and opert-scrub/pastures (0.42%), respectively, Subdivision-wise categorisation of degraded lands was also attempted for efficient location-speeific reclamation planning and easy monitoring.     

An assessment of a collaborative mapping approach for exploring land use patterns for several European metropolises

Until recently, land surveys and digital interpretation of remotely sensed imagery have been used to generate land use inventories. These techniques however, are often cumbersome and costly, allocating large amounts of technical and temporal costs. The technological advances of web 2.0 have brought a wide array of technological achievements, stimulating the participatory role in collaborative and crowd sourced mapping products. This has been fostered by GPS-enabled devices, and accessible tools that enable visual interpretation of high resolution satellite images/air photos provided in collaborative mapping projects. Such technologies offer an integrative approach to geography by means of promoting public participation and allowing accurate assessment and classification of land use as well as geographical features. OpenStreetMap (OSM) has supported the evolution of such techniques, contributing to the existence of a large inventory of spatial land use information. This paper explores the introduction of this novel participatory phenomenon for land use classification in Europe's metropolitan regions. We adopt a positivistic approach to assess comparatively the accuracy of these contributions of OSM for land use classifications in seven large European metropolitan regions. Thematic accuracy and degree of completeness of OSM data was compared to available Global Monitoring for Environment and Security Urban Atlas (GMESUA) datasets for the chosen metropolises. We further extend our findings of land use within a novel framework for geography, justifying that volunteered geographic information (VGI) sources are of great benefit for land use mapping depending on location and degree of VGI dynamism and offer a great alternative to traditional mapping techniques for metropolitan regions throughout Europe. Evaluation of several land use types at the local level suggests that a number of OSM classes (such as anthropogenic land use, agricultural and some natural environment classes) are viable alternatives for land use classification. These classes are highly accurate and can be integrated into planning decisions for stakeholders and policymakers.