Morpho-physical Properties of Soils of Kanamadi South Sub-watershed of Karnataka

An investigation was carried out to determine the morpho-physical status of soils of Kanamadi South sub- watershed in Karnataka state of India. A detailed soil survey of Kanamadi South sub watershed was carried out using IRS P6 LISS-IV image and a total of ten pedon location which were well distributed in Kanamadi South sub-watershed was selected. The soils were shallow to deep. Colour of pedons varied from 10 YR 2/1 (black) to 10 YR 4/3 (brown). Soil texture varied from clay to clay loam, having loose to moderately subangular to angular blocky in structure with few fine roots distributed in surface horizons. Generally, the clay content increased with depth. Consistency of soil pedons ranged from slightly hard to hard when dry, friable to firm when moist, slightly sticky to very sticky and slightly plastic to very plastic when wet. The maximum water holding capacity of soil horizons ranged from 59.65 to 79.15 per cent and generally increased down the depth. The bulk density of pedons varied from 1.17 to 1.37 Mg m-3. In general, bulk density varied with depth with lowest bulk density at surface and highest recorded in sub surface depths. The field capacity varied from 28.21% to 41.32 %.The morphological and physical properties study in area helps for resource inventorization for successful watershed planning for soil and water conservation to enhance the potential of fertility of soils and major fertility enhancement to increase the soil productivity.

Assessment of Temporal Change in Terrestrial Carbon Sequestration Capacity With Land Use Land Cover Change Along the Metro Corridor in Kochi, India

Kochi is undergoing drastic environmental changes with the developmental activities. Kochi metro rail project is one among them. The present study focuses on the decrease in carbon sequestration capacity due to clearing of vegetation, especially trees and paddy fields for metro rail. Metro rail corridor extends to a length of 18.22 km with 16 stations. Total extent of the study area is 777.7 ha covering 200 m buffer zone on both sides of metro corridor. This study integrates analysis of satellite images using GIS along with carbon inventory data from field surveys. IRS P6 LISS IV satellite sensor images of 26th February 2013 and 5th February 2017 are used for the study. Ground-truthing is done for 25 sampling plots. The study showed a total reduction of 35.8 ha of vegetation area which is converted into built-up area. The total carbon content is reduced by 6877 tons in an area of 777.7 ha ie: 8.84t/ha on an average. Maximum reduction has occurred along the metro rail and station zones, where maximum numbers of gown up trees were removed.

Application of geo-spatial technologies in soil suitability assessment for village level crop planning in Chittaurgarh, Rajasthan

The agro-eco-sub region (AESR) 4.2 encompasses Aravalli foot hills, central Rajasthan plains and adjoining areas. Visual interpretation of geo-coded satellite data (IRS-P6, LISS IV MX) on the same scale was done before starting the field work. Based on the interpretative units a high intensity detailed soil survey was carried out in cluster of ten villages of Bhadesar tehsil of Chittaurgarh district on cadastral map (1:4000 scale) and the soils were characterized with respect to landforms. In all, 14 soil series were established and assessed for soil site suitability for maize, wheat, mustard and soybean. Daulatpura-c series soils are suitable for maize, mustard, soybean, and Daulatpura-d soils for soybean and moderately suitable for other crops. Soils of Bagund and Narbadiya-a series are moderately suitable for maize and marginally suitable for other crops. The soils of Bhadsoda-b series are marginally suitable only for mustard but moderately suitable for all other crops. Soils of Parliya series are moderately suitable only for mustard crop and marginally suitable for remaining crops. The soils of Guda series are marginally suitable for maize, wheat, mustard but not suitable for soybean. The soils of Nardhari-a and Nardhari-b are moderately suitable, Daulatpura-b, Bhadsoda-a and Narbadiya-b are marginally suitable whereas soils of Madanpura and Daulatpura are not suitable for all the crops due to limitations of shallow soil depth.

Evaluating Changes in Land Use Land Cover using Remote Sensing Satellite Data and GIS (A Case Study in Patna Municipal Corporation Area) Patna, Bihar

Evaluation of land use land cover (LULC) change is an essential aspect of development in rural and urban sectors. This paper investigates the changes in LULC aspects of an environmentally vulnerable Patna Municipal Corporation (PMC) area in the middle-Ganga Plain, India. We offer Remote Sensing (RS), and Geographic Information System (GIS) techniques delineated LULC types include water bodies, agriculture land, fallow land, wasteland, built-up land and vegetation of the study area. LULC mapping of the study area was done through False Color Composite (FCC) Satellite image Resourcesat-1 (IRS P6 LISS-IV) and Resourcesat 2A (IRS-R2A LISS-IV) with 5.8-meter spatial resolution data of the year 2007 and 2018 respectively. The supervised classification and maximum likelihood equation were used to classified two multi-temporal images. Then temporal changes were detected by comparison between two LULC classified maps of 2007 and 2018, which was produced independently. Patna Municipal Corporation (PMC) area, Patna is one of the environmentally vulnerable areas under the threat of environmental and ecological degradation as a result of human activities due to improper land cover management. The main objective of using change detection is an important technique to detect changes in LULC over time in PMC, Patna between 2007-2018, and it is significant for updating land cover or natural resource management. The interpretation of this study has substantial changes in LULC occurred in the Patna Municipal Corporation (PMC) area, Patna within the period 2007-2018, related to urbanisation and economic development. The analysis outcome indicates the most remarkable changes occurred an increase in Built-up, (+) 21.86 % between 2007-2018, whereas the area of cropland and vegetation decreased (-) 8.95 % and (-) 5.8% respectively between 2007-2018. In the spatial distribution pattern, other changes have also occurred. This study will give the benefit in future action plans in land use and urban development and avoid LULC changes without proper planning. It will be most significant for the natural environment.

Land Use/Land Cover Change Detection using Geoinformatics in Gurugram District, Haryana, India

The district Gurugram in the state Haryana has seen significant extension & development during the last few years. In this paper, the change in land-use/cover has been estimated with time range of 2007 - 2017 and the change detection was quantified. The land-use/cover data generated through satellite imagery has been classified into five major classes i.e., (i) Built-up land (ii) Water Bodies (iii) Barren Land (iv) Agricultural Land (v) Vegetation. The investigation was helped out through Geoinformatics approach by using IRS-P6- LISS-III sensor of 2007 and IRS-P6-LISS-IV sensor of 2017. Observing of land-use/spread mirrored that changes were more noteworthy in degree over the time range of 10 years in the land under various classes. The most sensational changes are the increase in built-up land and barren land. Apart from this decrease in agricultural, water bodies and vegetation cover area also. Results demonstrates an expansive change in the territory of various land use classifications amid the period from 2007 to 2017.The agriculture land covering an area of about 55.27% in 2007 reduced to 43.42% in 2017. The built up area increased from 15.97 % in 2007 to 30.23 in 2017. The barren land area increased from 6.45 % in 2007 to 16.97 in 2017 The Water bodies decreased from 4.65 % in 2007 to 1.05 % in 2017. The vegetation area has also decreased from 17.66 % in 2007 to 8.33 % in 2017. Urban extension and various anthropogenic exercises have brought genuine misfortunes of agricultural land, vegetation and water bodies.

Characterization and Classification of Soils of Jirang Block in Meghalaya Plateau

The Meghalaya plateau occupying a major portion of entire state of Meghalaya remains as an important part of the ancient Deccan plateau. A detailed soil survey (1:10,000 scale) of the Jirang block of Ri-Bhoi district was carried out using IRS-P6 LISS IV and Cartosat-1 images. Typical pedons representing major landforms of the study area viz., denudational hills, plateau and inter hill valley plain developed from granite–gneiss occurring under varying land use were characterized, classified and assessed. The soils were deep to very deep, dark grayish brown to red in colour, extremely acid to moderately acid in reaction and high in organic carbon; the latter decreased with increase in depth. Soils on high denudational hills, highly dissected upper and lower plateau and lowly dissected lower plateau are highly weathered (kandic horizons) with base saturation <35% and are classified to Ultisols. Soils on low denudational hills are highly weathered Alfisols. Soils of moderately dissected lower plateau and those on upper valley region are both Alfisols, but the latter has lower base saturation than the former. The soils of the lower valley are Alfisols with an aquic moisture regime.

LANDSLIDE IDENTIFICATION FROM IRS-P6 LISS-IV TEMPORAL DATA-A COMPARATIVE STUDY USING FUZZY BASED CLASSIFIERS

<p><strong>Abstract.</strong> While extracting land cover from remote sensing images, each pixel in the image is allocated to one of the possible class. In reality different land covers within a pixel can be found due to continuum of variation in landscape and intrinsic mixed nature of most classes. Mixed pixels may not be appropriately processed by traditional image classifiers, which assume that pixels are pure. The existence of mixed pixels led to the development of several approaches for soft (often termed fuzzy in the remote sensing literature) classification in which each pixel is allocated to all classes in varying proportions. However, while the proportions of each land cover within each pixel may be predicted, the spatial location of each land cover within each pixel is not. Thus, it is important to develop and implement a classifier that can work as soft classifiers for landslide identification. This work is an attempt to document and identify landslide areas by five spectral indices using temporal multi-spectral images from IRS-P6 LISS-IV images. To improve the spectral properties of spectral indices for specific class identification (in this case landslide) a Class Based Sensor Independent (CBSI) technique proposed. The result indicates that CBSI based Transformed Normalized Difference Vegetation Index (TNDVI) temporal indices data gives better results for landslide identification with minimum entropy and membership range.</p>

Identifying Possible Locations to Construct Soil Water Conservation Structures by Using Hydrogeological and Geospatial Analysis

Identification of soil water conservation structures (SWCs) necessitates as the proximity of study area (Shivganga watershed) to the Western Ghats imparts high rainfall and runoff, resulting to accelerate soil erosion. To decrease soil erosion and improve water storage as well as recharge, the investigation of new possible structures is necessary. With this intent, suitable sites for SWC structures (check dam and percolation ponds) were identified by using hydro-spatial data such as soil, land use/cover, slope, runoff, infiltration data from IRS P6 LISS-IV imagery and other collateral data. Further, acquired data were processed to derive runoff by employing Soil Conservation Service Curve Number (SCS-CN) method and infiltration by Allen (2008) method. The Integrated Mission for Sustainable Development (IMSD) specifications were used for the identification of locations for constructing SWC structures. The results revealed that about 28% area is suitable for implementation of SWC structures. Total 45 locations SWC structures were derived with the present method, out of that 20 were already built. The superimposition of derived and existing locations shows (80-100%) accuracy, authenticates the reliability of the method. The present modified method will definitely help in speedy identification of a location for SWC structures.