Detecting Forest Fire Prone Areas Using Object-Based Image Analysis and GIS Techniques： A Case Study in Kayer Khola, Nepal

Every year during summer, natural and human-induced forest fires threaten the environment in the largely forested areas of the Himalayan region and the local population living near these forests. Nepal, with its multitude of forests, is one of the most forest fire-prone areas in the region. This study examines the possibility of averting forest fires, minimizing their frequency and the damage they cause, through advanced mapping of forest fire prone areas using a VHSR （very-high spatial resolution） satellite image of GeoEye-1, DEM （digital elevation data） created from topographic maps and additional data layers （e.g., precipitation, settlements）. The study was conducted in Kayer Khola, Chitwan district, Nepal. The classification of the satellite image has been performed using OBIA （object-based image analysis） techniques taking into account spectral, spatial and context information as well as hierarchical properties. The land cover classification result was thereafter combined with additional data in ArcGIS, where the input layers were reclassified and all classes of the input layers ranked according to their proneness to forest fires. Fire prone areas were delineated in five classes ranging from very high to very low. The study revealed that 82% of fires occur in forest areas. This case study in Kayer Khola shows that OBIA and GIS modeling techniques can be used to successfully identify forest fire-prone areas. The mapping of forest fire-prone areas will enable forest departments in countries of the Himalayan region to delineate forest fire prone areas, which can guide the forest departments set up appropriate fire-fighting infrastructure in these areas and thus help, minimize or avert forest fires.

Morphometric Analysis of Kakoi River Watershed for Study of Neotectonic Activity Using Geospatial Technology

Morphometric analysis is defined as the quantitative measurement of landscape shape. Morphometric studies of a watershed helps the researcher to compare different landform and calculate the geomorphic indices that may be useful for identifying a particular characteristic such as the level of neotectonic activity in a watershed. The present study has been carried out in Kakoi River Watershed which is a part of Lower Subansiri River Basin in Assam. The study area is geo-dynamically unstable region characterized by active faults, continuing crustal movements and complicated structural region which fall under the seismic zone V of India. In recent century, the Lower Suabsiri River Basin has gone tremendous morphological changes due to active tectonics activities. After the Assam Earthquake of 1950, some of the rivers like Subansiri and its tributaries Dirgha, Kadam and Kakoi suddenly changed their channels giving birth to new channels. The present study is to examine the neotectonic domains and the changes of river course. The geomorphic indices such as Hypsometric Integral (HI), Elongation ratio (Re), Asymmetry Factor (AF), Stream-length Gradient Index (SI), Mountain Front Sinuosity (Mfs), Basin shape index (Bs), Ratio of Valley floor width to Valley Height (Vf) and Channel sinuosity (S) etc. have been studied from remote sensing data. The results shows that the study area is under active tectonic area based on Vf (0.301), Rl (0.461), Bs (3.6), Sl (165.73) and other parameters such as S (1.38) and Mfs (2.02) indicated as moderate active tectonic region. Utilization of geospatial technology and remote sensing data in the present study becomes more reliable and helpful in analyzing, monitoring and understanding the landform changes in a watershed.

Landslide Hazard Zonation Mapping in Ghat Road Section of Kolli Hills, India

Landslides are the most common natural disaster in hilly terrain which causes changes in landscape and damage to life and property. The main objective of the present study was to carry out landslide hazard zonation mapping on 1:50,000 scale along ghat road section of Kolli hills using a Landslide Hazard Evaluation Factor(LHEF) rating scheme. The landslide hazard zonation map has been prepared by overlaying the terrain evaluation maps with facet map of the study area. The terrain evaluation maps include lithology, structure, slope morphometry, relative relief, land use and land cover and hydrogeological condition. The LHEF rating scheme and the Total Estimated Hazard(TEHD) were calculated as per the Bureau of Indian Standard(BIS) guidelines(IS: 14496(Part-2) 1998) for the purpose of preparation of Landslide Hazard Zonation(LHZ) map in mountainous terrains. The correction due to triggering factors such as seismicity, rainfall and anthropogenic activities were also incorporated with Total Estimated Hazard to get final corrected TEHD. The landslide hazard zonation map was classified as the high, moderate and low hazard zones along the ghat road section based on corrected TEHD.

Using object-based analysis to derive surface complexity information for improved filtering of airborne laser scanning data

Airborne laser scanning （ALS） is a technique used to obtain Digital Surface Models （DSM） and Digital Terrain Models （DTM） efficiently, and filtering is the key procedure used to derive DTM from point clouds. Generating seed points is an initial step for most filtering algorithms, whereas existing algorithms usually define a regular window size to generate seed points. This may lead to an inadequate density of seed points, and further introduce error type I, especially in steep terrain and forested areas. In this study, we propose the use of object- based analysis to derive surface complexity information from ALS datasets, which can then be used to improve seed point generation. We assume that an area is complex if it is composed of many small objects, with no buildings within the area. Using these assumptions, we propose and implement a new segmentation algorithm based on a grid index, which we call the Edge and Slope Restricted Region Growing （ESRGG） algorithm. Surface complexity information is obtained by statistical analysis of the number of objects derived by segmentation in each area. Then, for complex areas, a smaller window size is defined to generate seed points. Experimental results show that the proposed algorithm could greatly improve the filtering results in complex areas, especially in steep terrain and forested areas.

Improved Cubemap model for 3D navigation in geo-virtual reality

Due to advances in rendering techniques and hardware capability,stereoscopic 3D(s3D)visualization is becoming increasingly common in daily life.However,this does not change the fact that stereo effects and visual comfort depend greatly on how the related parameters are controlled during the production of the s3D images.In geovirtual reality systems,which are important browsers for Digital Earth,the maintenance of these parameters is deeply related to the navigation process.Therefore,the navigation method in such systems requires special care.This paper presents a new flying method based on a Cubemap structure.The method defines a Vehicle model and modifies the original Cubemap structure by adding a front view camera during the navigation;it allows the users to fly through a virtual geographic environment with automatic speed control,smooth collision resolution,and dynamic adjustment of the s3D-related parameters.A user test was conducted to compare this new method with the original method based on the Cubemap structure.The results show that the new method performs better than the former one for it provides a convenient interaction experience with improved stereoscopic effect,and diminishes visual discomfort.

A stream-based Parasitic Model for implementing Mobile Digital Earth

A Parasitic Model is proposed in this study for Digital Earth running on mobile phones through a mobile network.Because of mobile phones’limited capabilities in high-performance computing,rendering,storing,and networking(CRSN),these functions are accomplished by a superior host computer in this model.Rendered virtual scenes are compressed in a time-series as a data stream and are sent to the mobile phone through a mobile network,thus allowing Digital Earth to be operated on a mobile phone.This study examines a prototype and shows that a Mobile Digital Earth based on a Parasitic Model can achieve functionality beyond the mobile phone’s actual hardware capabilities and can reduce network traffic.These results demonstrate quasi-real-time interactions,but with bandwidth increases in next-generation mobile networks such as 4G and 5G,there is potential for real-time interactions in the near future.