Arid region of India shows vast variation in climate and vegetation during last two decades. In order to analysis impact of monsoonal patterns on the vegetation indices of the arid zone, a three years (2015-2017) temporal series Moderate Resolution Image Spectrometer (MODIS) data for Pre & Post Monsoon was used for computing Normalized Difference Vegetation Index (NDVI). The cloud-free NDVI time series data are used to study the relationship between the rainfall pattern and the vegetation changes in Jodhpur District. ENVI and ArcGIS image processing software are used to evaluate and monitor the vegetation for the pre-monsoon and postmonsoon seasons for three years. Enormous changes were observed during pre and post monsoon temporal analysis. This study shows that MODIS NDVI data is best suited for quick vegetation assessment in arid region.
<p><strong>Abstract.</strong> Land Use – Land Cover (LULC) classification mapping is an important tool for management of natural resources of an area. The remote sensing technology in recent times has been used in monitoring the changing patterns of land use-land cover. The aim of the study is to monitor the LULC changes in Jodhpur city over the period 1990–2018. Satellite imagery of Landsat 8 OLI (June, 2018) &amp; Landsat TM (Oct, 1990) were used for classification analysis. Supervised classification-maximum likelihood algorithm is used in ENVI software to detect land use land cover changes. Five LULC categories were used, namely- urban area, mining area, vegetation, water bodies and other area (Rock outcrops and barren land). The LULC classified maps of two different periods i.e. 2018 and 1990 were generated on 1<span class="thinspace"></span>:<span class="thinspace"></span>50,000 scale. The accuracy assessment method was used to measure the accuracy of classified maps. This study shall be of good assistance to the town planners of Jodhpur city for the purpose of the sustainable development as per the master plan 2031.</p>
Exhaust emission analysis from diesel vehicles has received a lot of attention in recent times in the context of implementation of Bharat Stage-IV norms and thermal signature analysis for civil and military applications. The exhaust emission thermal IR signatures of military diesel vehicles such as truck and bus using a gas analyser and thermal imager under idling and accelerating conditions of these vehicles is investigated. Concentration and temperature of diesel exhaust emission CO, NOx, and HC remains almost constant during engine running in idle condition and varies with the engine acceleration. Exhaust gases maximum temperature reaches in the range of 240 °C -270 °C during engine acceleration. A detailed investigation of thermal signature in mid wave infrared, 3 µm -5 µm waveband and long wave infrared, 8 µm -14 µm waveband is also presented under the same engine running conditions. Thermal image analysis exhibited that the area of thermal IR image of diesel vehicles truck and bus has been increased 0.077 per cent and 0.594 per cent, respectively with the engine acceleration. It has been observed that thermal signature of exhaust gases is a good tool for vehicle exhaust emission visualisation and analysis.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.