Faculty Publications
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Item Post processing and analysis of storm surge: A case study of Hudhud and Phailin cyclones(International Society for Photogrammetry and Remote Sensing, 2018) Konkathi, K.; Murty, P.L.N.Tropical cyclones affect the east coast of India due to its distinctive topography which is formed with a network of estuaries, bays, rivers, and inlets that causes inland flooding. The inland inundation of sea water is inflicting severe damage to the life and property. The ocean water entering the beachfront zone results to storm surges. In order to mitigate these storm surges, real-time monitoring and warnings are essential. For better visualization and analyzing the outputs from storm surge models, efficient post-processing tools are required. Hence post-processing of storm surge using GIS is carried out for taking protective measures. Storm surge vulnerable locations along the east coast of India have been identified in perspective of the number of storm surge events. Blue Kenue and SMS softwares are used to generate the unstructured triangular mesh over the study domain. Cyclones Phailin and Hudhud are selected in the current study and the associated surge heights and inundation extents are examined. © 2018 International Society for Photogrammetry and Remote Sensing. All Rights Reserved.Item Assessment of Burn Severity using Different Fire Indices: A Case Study of Bandipur National Park(Institute of Electrical and Electronics Engineers Inc., 2019) Konkathi, K.; Shetty, A.Forest fires are the significant catastrophic events which affect the landscape and vegetation in forested lands. They cause loss of biodiversity, land degradation & ecological imbalance. As the forest fires cause high damage to the habitat, it is of utmost necessity to assess the impact of fire. Burn severity mapping contributes to the evaluation of fire severity and extent of burnt areas. In this article, recently occurred forest fire (21st to 25th February 2019) in Bandipur national park was assessed using remote sensing techniques for mapping burnt area and burn severity as on-site estimations are highly impossible during forest fires. Three established fire severity indices differenced normalized burn ratio (dNBR), relativized burn ratio (RBR) and relativized dNBR (RdNBR) are assessed and compared based on number of active fire points provided by MODIS & VIIRS. The RdNBR resulted in an accuracy of 89.14% whereas RBR and dNBR produced an efficiency of 52.48% and 60.633% respectively. The burnt area under high severity was around 4099 hectares. Post-fire assessment is an essential element for finding the effects of fire on vegetation and implementing mitigation strategies. © 2019 IEEE.Item A Comparative Analysis of Forest Fire Risk Zone Mapping Methods with Expert Knowledge(Springer, 2019) Yathish, H.; Athira, K.V.; Konkathi, K.; Umesh, U.; Shetty, A.Despite repeated occurrences of forest fire, very less scientific studies have been reported in the Indian context especially in Kudremukh region to mitigate and suppress the fire. The objective of this article was to pool the expert knowledge on forest fire triggering factors from officials working in wildlife division in the Western Ghats of India through a questionnaire and to validate the risk zones obtained from three popular fire risk zone mapping methods namely logistic regression, multi-criteria decision analysis, and weighted overlay. Based on the earlier studies and expert knowledge, fire ignition parameters considered are elevation, slope, and aspect, proximity to roads, water bodies and area of human activities, normalized difference vegetation index (NDVI), land surface temperature (LST), and vegetation type. The regression model was based on previous fire occurrences and the other two based on expert’s opinion. The three models were validated and compared using past fire occurrence events. The logistic regression model gave 88.89% of accuracy and that of multi-criteria decision analysis with 74.6% accuracy, and that of weighted overlay method with an accuracy of 68.24% for the specific study area. The logistic regression model is useful in the presence of historical data, whereas expert knowledge is helpful for mapping risk zones using multi-criteria decision analysis and weighted overlay analysis when historical data are scarce or not available for mapping risk zones. The obtained risk maps can be used for deciding watchtower locations, installation of sensors, cameras, etc. In every forest division, it is recommended to prepare a standard questionnaire form and document their experiences on forest fire in the region under their supervision before they are getting transferred to another location. © 2019, Indian Society of Remote Sensing.Item Evaluating the effects of forest fire on water balance using fire susceptibility maps(Elsevier B.V., 2020) Venkatesh, K.; Konkathi, K.; Ramesh, H.Sudden and long term changes in the landscape can be attributed to periodic wildfires which, is a cyclic occurrence at Kudremukh national forest in Western Ghats of India. These land-use changes influence the hydrology of landscape, causing disintegration of soil, loss of biodiversity, changes in stream and flooding. To understand and account for these land-use changes, a new approach was implemented by developing fire susceptibility map from topographic, climatic and human-induced factors and validating it with MODIS (Moderate-resolution Imaging Spectro-radiometer) fire points for discretising accuracy. The fire susceptibility map can be used for studying the long-term (year or more) effects of fire on water balance systems. The fire susceptibility map generated for the years 2005 and 2017 was overlaid with MODIS LULC (Land Use Land Cover) for establishing the post-fire scenario whereas MODIS LULC MCD12Q1 (2005 and 2017) was considered as the no-fire scenario to analyse the intensity of the fire and its effect on streamflow and infiltration. These maps along with historical satellite hydro-climatic datasets, were used to assess the effect of forest fire on hydrological parameters using the SWAT (Soil and Water Assessment Tool) model. No-fire and post-fire conditions were established by modifying SCS-CN (Soil Conservation Service-Curve Number) based on previous works of literature to represent the catchment as unburnt and burnt area. The SWAT model was calibrated (2002–2008) and validated (2009–2012) for establishing a baseline scenario. The sensitive parameters obtained from SUFI-2 (Sequential Uncertainty Fitting) algorithm in SWAT-CUP (Calibration and Uncertainty Programs) were used to simulate stream flows till 2017 due to lack of observed streamflow data for the year 2017. It was inferred that the effect of wildfire on flows in recent years (2017) had increased radically when compared to the flows before a decade (2005), diminishing the rate of infiltration and causing the deficit in groundwater to energise. The methodology can further be executed in any forest area for distinguishing fire hazard zones and implementing prior actions in those areas for mitigation of forest fires and maintaining sustainable water balance. © 2019 Elsevier Ltd