Abstract: Remote Sensing as well as Space Technology has a spin off benefit in the socio-economic uplift of the countries that has it. It promotes the quality of life of the whole society. Food security means that everyone should get enough food throughout the year to satisfy their nutritional needs. Bangladesh is an agricultural country .Its development and economy depends predominantly on agriculture as well as food security. Rice is the main crop of the country. The main rice is Aus, Aman and Boro which is produced in every part of Bangladesh. The crop monitoring using the Remote Sensing Technology and Geographic Information System (GIS) has a great potential to provide the near real time information on crop growth condition, production and damage of crops due to natural disasters like cyclone, flood, drought etc. Timely and accurate information about the natural resources like crops as well as environmental conditions play a significant role towards food security .It helps the decision-aids of disaster management and national food security policy for the sustainable development of the country. Space Research and Remote Sensing Organization (SPARRSO) conducts monitoring of crop and weather in this regard regularly. In this paper, crop monitoring using Remote Sensing Technology towards food security of Bangladesh, will be discussed.
ABSTRACT: In the past two decades, Addis Ababa City emerged as one of the fastest urbanizing cities in the East African Sub Saharan region. In the absence of a regular use of geospatial information management systems, limited effort had been made to keep track of changes in the natural environment in the rapidly growing city for policy making in land administration. The ubiquitous energy radiated by the rapid urbanization rate in the area not only created unprecedented consequences by diminishing the quality of the environment and natural resources but it raises serious implications for land management in the city. The factors fuelling the land crisis in the area which are not farfetched consists of socio-economic, ecological and policy elements. To tackle these issues in a mega city, up-to-date knowledge would be required to capture and analyze land information trends. Such an effort will help manage the city’s expansion as well as infrastructure development through the right choices in planning and (spatial) designs using the latest tools in geospatial technologies of Geographic Information Systems GIS) and remote sensing. This study investigates the spatial implications of the rapid expansion of metropolitan yeka subcity for land management using GIS and Remote sensing technology. The result of the research provides a valuable road map that can enable planners contribute to improved land administration necessary for effective management of natural resources.
Control of cotton stalk regrowth with herbi- cides on standing or shredded cotton provides an alternative method for post-harvest destruction of cotton stalks. Field experiments were conducted in 2002 and 2003 in the Rio Grande Valley of south Texas to assess the effectiveness of different herbicide treatments for cotton regrowth control using remote sensing technology. Eight treatments (combinations of herbicides and application tim- ings) in 2002 and six treatments in 2004 arranged in a randomized complete block were evaluated on shredded cotton plots. Airborne color-infrared (CIR) imagery was acquired from the test plots in both years shortly before the state-mandated date for cotton destruction. Ground reflectance spectra and visual ratings ranging from no live plants to mostly healthy plants were also obtained from each plot. The reflectance spectra showed dif- ferences in regrowth among the treatments. The airborne CIR imagery provided limited visual differentiation among the treatments because of the small amount of regrowth. For quantitative analysis, the green, red, and near-infrared bands of the CIR imagery and four vegetation indices derived from the three bands were used as spec- tral variables to compare the differences among the treatments for each experiment. Statistical analysis showed that the spectral variables were able to identify the differences among the treat- ments as detected by the ground observations.
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The major cause of drought is low precipitation level, which often recurs every cold season until hot season (Laosuwan et al., 2016). Water defi- ciency affects to vegetation phenology which will be, in turn, indicate the drought severity level (Wattanakij and Mongkolsawat, 2008; Laosuwan et al., 2016). Remote sensing technology is mod- ern and up-to-date technology that is able to ap- ply for many situations especially natural disaster prediction such as drought, flooding, soil erosion and etc. (Laosuwan and Rotjanakusol, 2013; Lao- suwan and Uttaruk, 2014; Yannawut and Teera- wong, 2017; Teerawong and Yannawut, 2017; Dušan et al., 2017).
The remote sensing technology of unmanned aerial vehicle (UAV) is a low altitude remote sensing technology. The technology has been widely used in military, agricultural, medical, geographical mapping, and other fields by virtue of the advantages of fast acquisition, high resolution, low cost, and good security. But limited by the flying height of UAV and the focal length of the digital camera, the single image obtained by the UAV is difficult to form the overall cognition of the ground farmland area. In order to further expand the field of view, it is necessary to mosaic multiple single images acquired by UAV into a complete panoramic image of the farmland. In this paper, aiming at the problem of UAV low-altitude remote sensing image splicing, an image mosaic technique based on Speed Up Robust Feature (SURF) is introduced to achieve rapid image splicing. One hundred fifty ground farmland remote sensing images collected by UAV are used as experimental splicing objects, and the image splicing is completed by the global stitching strategy optimized by Levenberg-Marquardt (L-M). Experiments show that the strategy can effectively reduce the influence of cumulative errors and achieve automatic panoramic mosaic of the survey area.
Realizing the importance of Remote sensing technology in Disaster management the State Remote Sensing Application Centre, Itanagar (SRSAC), completed Hazard Zonation of Arunachal Pradesh pertaining to landslides, floods and earthquake on 1:50K scale (DMIS, 2008). The term "landslide" refers to the downward and outward movement of slope-forming materials like rocks, soil, sediments, artificial fills or a combination of these (Varnes, 1978). The Landslide Hazard Zonation (LHZ) maps on 1:50K scale is the first attempt by SRSAC to find out the vulnerable zones in Arunachal Pradesh as per the guidelines suggested for landslide hazard zonation in mountainous terrain by the Bureau of Indian Standards (BIS 1998). Major factors that influence the occurrence of landslides are lithology, structure, slope, geomorphology, land use/land cover, forest density, relative relief, anthropogenic reasons and rainfall (Fig.2). Slope facet, which is defined as a part of hill slope having more or less similar characters of slope showing consistent slope direction and inclination is considered as the smallest unit for the study (DMIS, 2008). Cumulative weightages were calculated by adding ratings of individual sub-parameters for each facet. Based on the cumulative weightages the LHZ is classified into five hazard zones such as very high, high, moderate, low and very low (Fig.3). The methodology was validated by overlaying the landslide incidence map over the LHZ map (DMIS, 2008). The LHZ maps are important macro-scale (1:50K) information for all the developmental projects in the state for analyzing and designing the new projects against the possible landslide threat. For that reason the database was shared with all the State Government line departments and to the Govt. of India programme, ‘National Database for Emergency Management Mission (NDEM)’. In Figure 3, the high-resolution satellite image shows the active landslide at Karsingsa on National Highway 52A. This landslide falls in the very high hazard zone in the LHZ map. The Karsingsa landslide is active in nature owing to continuous toe cutting by the Dikrong river. The flow of land mass at Karsingsa is termed as static liquefaction by Sharmah and Singh (2011). Several research institutions are engaged in research for management and mitigation of Karsingsa landslide including early warning yet almost every year the community face crisis at Karsingsa.
Remote Sensing is the process involving an interaction between incident radiation and the targets of interest. Multispectral data of Jakarta comes from Landsat 7 satelite. Data is aquired by 7 spectral band sensor which covers visible, near infrared, and mid infrared spectrum. The spatial resolution of band 1 - 5, and band 7 are 30 m, the resolution of the sixth band is 60 m. Jakarta area is large (approximately 649.71 km 2 ), that is more than 700.000 pixels. An each pixel contains seven channels of multispectral data. It means that an each pixel has seven digital numbers.
The use of remote sensing techniques in the analyses of droughts is based mainly on employ- ing spectral indicators for determining the condi- tion of the vegetation (vegetation health) [Nico- lai-Shaw et al. 2017, Dąbrowska-Zielińska et al. 2011]. Connecting the reflection of light with the biophysical characteristics of plants enabled to use the spectral indicators for assessing biomass production, forecasting of yields, and susceptibil- ity of plant organisms to the influence of stressors such as water retention in the soil. It is possible to use plants as indicators in the study of soil-plant environment moisture [Dąbrowska-Zielińska et al. 2011], and thus in the assessment or even pre- diction of drought. Normalized Difference Vege- tation Index (NDVI) [Pettorelli et al. 2005, Huete et al. 2002] is one of the most recognized and de- scribed spectral indices. This index is calculated based on the difference between reflectance of sunlight in the near–infrared and red bands nor- malized by the sum of both of them [Wójtowicz et al. 2005]. Its basic function is determining the amount of chlorophyll in the plants cells. Accord- ing to this parameter, it is possible to determine the condition of the plant and its susceptibility to external stressors [Carlson and Ripley 1997]. NDVI can be used as a substitute indicator for as- sessing the water content in the environment be-
While spatial and spectral information is extracted by optical remote sensing, radar remote sensing in the microwave frequency band also provides an irreplaceable source of information for HR Earth observations with both day and night imaging capability (Park, 2015). SAR images can provide a wealth of geological and mineral information such as geological structure, lithology, and hidden geological bodies, especially related to volcanic deposits, meteorite impacts, and large faults [78,79,80,81]. The real time quantitative measurement of crustal deformation can be obtained by using ground Sentinel-1 images obtained at different times. In fact, the analysis of Sentinel-1 data has become routine by participating national and international agencies in seismic research, earthquake disaster assessment, and civil defense activities. The main aspects of earthquake analysis using Sentinel-1 data include:
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receive this type of training (Cabello et al. 2012; Pettorelli et al. 2014). Conceptual models of ecosystem functions are a possible nexus of ecosystem process and remote sensing expertise (see Fig. 2), similar to and/or informed by the conceptual ecosystem models developed as part of Red List of Ecosystems assessments (Bland et al. 2016). Potential differences in the conceptual understanding of causality in the drivers of ecosystem processes across dis- ciplines may in this way become apparent, and clarity of understanding promoted across different foci of expertise. By making the variables underpinning ecosystem func- tions and the relationships between them explicit, such models can help identify a minimum set of agreed vari- ables needed to monitor a given ecosystem function. Opportunities for monitoring these variables via remote sensing could then be systematically identified, focussing on user needs, and gaps in monitoring capacity priori- tized. Ultimately, without common references and defini- tions, and centralized, jointly developed platforms such as these, rapid advances are unlikely.
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Satellite images provide various statistical analysis of forest cover and the information about deforestation using GIS maps. Satellite remote sensing allows a fundamental data for observation and for calculating deforestation effect The Geographical Information Systems (GIS) is an information technology that has been used in public policy making for environmental and forest planning and decision making in forest management using ICT technologies [1, 3]. The use of Geographical Information Systems (GIS) has increased significantly in engineering, natural and ecological sciences applications, offering accurate, efficient, reproducible methods for collecting, view in g and analyzing spatial data. The GIS helps in dealing with data and information complexity. The evolution of GIS, the Global Positioning System (GPS), and Remote Sensing (RS) technologies and Data Sciences, Information Systems, and MIS has enabled the collection and analysis of field data and provide deep insight and helps in forest management.
 J. Suresh Babu, Prof. T.sudha, “Hybrid Algorithm For Deforestation Detection Using Satellite Data”, International Journal of Management, IT & Engineering Vol. 6 Issue 10, ISSN: 2249-0558 Impact Factor: 6.269, pp. 27-33, October 2016.  J. Suresh Babu, Prof. T. sudha, “Hybrid Algorithm for Deforestation Detection Using Satellite Data by Using Support Vector Machine (SVM) Algorithm”, International Journal of Emerging Research in Management &Technology ISSN: 2278- 9359 (Volume-6, Issue-6) pp.92- 97, June-2017.
Recently certain methods have been developed to integrate encryption and watermarking for protecting digital images, which can guarantee security. This algorithm takes advantage of the feature of spatial scrambling in only disordering the arrangement of protected data, which essentially would not disturb the embedding of watermark by modifying carrier data, to achieve the integration of en-cryption and watermarking. However, this integration algorithm is only available for spatial scrambling. proposed a method to integrate encryption and watermarking by embedding mark with the decrypting simultaneously, which took advantage of the slight difference between encryption key and decryption key to gain an imperceptibly different plain text to achieve mark embedding. However, for the remote sensing images, this method provides only one kind of security protection at a time.Hence the encrypted remote sensing image doesn't bear the watermark and the watermarked image will be visible to everybody.
Remote sensing not only provides a wide-range scale of the space-time distribution of observations, but also saves time and money (Murthy, 2000; Leblanc et al., 2003; Tweed et al., 2007). In addition it is widely used to characterize the earth surface (such as lineaments, drainage patterns and lithology) as well as to examine the groundwater recharge zones (Sener et al., 2005). To understand groundwater prospects of an area, integration of different thematic layers is required. In the hard rock terrain, availability of groundwater is limited and its occurrence is essentially confined to fractures and/or weathered horizons (Krishnamurthy et al. 2000; Chandra et al. 2006; Vijith, 2007; Suja Rose and Krishnan, 2009).
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ABSTRACT: Tectonism induced liquefaction can be a major disaster that warrants appropriate emphasis in any infrastructure development planning. Various procedures and methods are applied throughout the world to identify potential zones of liquefaction. The output results are used as tools for site selection and finding viability of funding in infrastructure development. Thus such measure is slated to preclude future loss of life and property owing to infrastructure collapse by earthquake induced liquefaction. Liquefaction is likely to occur due to saturated soils or unconsolidated sediments under the infrastructure basement that are subjected to give way due to ground shaking. Liquefaction is one of the main geohazards related to tremor. The present study aims at assessing different soil properties and geological structures of Morobe and Madang Province culminating in delineation of Liquefaction potential zones using multi-criteria evaluation and Analytical Hierarchy Process (AHP) appraisal using GIS and Remote sensing technologies. The main data layers that are chosen for carrying out the assessment consist in available geological, soil and SRTM DEM data. Several thematic layers are prepared from the data base as mentioned, followed by assigning weightage to each thematic layer generated. Weightages were further normalized using Saaty’s analytical hierarchy process. The final Liquefaction potential zone was prepared using the raster calculated from ArcGIS. The output liquefaction potential zone map was delineated and reclassified into five categories such as ‘very high', ‘high', ‘moderate', ‘low’ and ‘very low’ potential zones.
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11. Rokade V. M. Kundal R. and Joshi A.K. (2004) “Water Resources Development Action Plan Sasti Watershed, Chandrapur District, Maharashtra Using Remote Sensing and Geographic Information System”, Journal of the Indian Society of Remote Sensing, Vol. 32, No. 4, 2004 12. Rokade V.M. (2003) “Integrated Geological Investigations for Groundwater Potential and water resource management of Sasti watershed, Taluka Rajura of Chandrapur District (MS) using Remote Sensing and GIS”, Published Doctorate thesis, Nagpur University, Nagpur
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A mobile ad hoc network (MANET) is an infrastructure less network with autonomous mobile nodes. The easily configurable and deployable properties of MANET make it suitable for the situations were a fixed infrastructure is not available or infeasible. However the dynamic movements of the mobile clients may disconnects the connectivity of the network frequently. This disconnection reduces the data accessibilities and later results in partitioning of the network. Thus the network partition problem makes the MANET unsuitable for the mission critical applications were the team members need to work in group and scattered in the application terrain. To overcome this principle challenge here introduces a new class of ad hoc network called Autonomous Mobile Mesh Network (AMMNET). AMMNET consist of mobile mesh nodes that can dynamically adapt to all topological changes of client movements. Since this network is infrastructure less, the performance and lifetime of the network depends on energy level of the nodes. Also the depletion of energy of the intermediate node may disrupt the entire communication of the network. This paper proposes a hybrid PSO-GA algorithm for finding an energy efficient path for routing in AMMNET. The simulation results shows that this hybrid algorithm provides better throughput and are more efficient than the standard PSO and genetic algorithms.
Spectrum sensing: detection time, frequency, space on the available spectrum, to determine the present can be used for transmitting and receiving channel, through the local spectrum sensing technologies and distributed detection, and using the spectrum hole detection method to reliably perceived large bandwidth within each sub channel is occupied, if for the authorized frequency band, so that cognitive users the main user system without causing interference access idle frequency band, make full use of limited spectrum resources; unauthorized band, capable of dynamic frequency selection, to ensure CWMN network working frequency band from the other types of equipment interference effects, but also reduce the interferences to other devices, that is to solve the problems of coexistence. Channel estimation: estimating the communication between the user channel quality, emission parameters (power, bit rate, coding mode); the establishment of the link, through the analysis of the communication process the received data packet to estimation of channel quality.
Abstract: This paper proposes an IR camera system that performs the task of removing mines for humanitarian purposes. Because of the high risks involved, it is necessary to conduct mine detection from the most remote endeavoring. By making use of infrared ray (IR) cameras, scattered mines can be detected from remote locations. In the case of mines buried in the ground, detection is possible if the peripheral temperature difference is large enough between the ground and mine weapon. Tests with trial mines were used to study the detection characteristics of IR cameras for images and various technologies for collecting and processing image data in real time for optimum mine detection.
Agricultural resources are important renewable dynamics natural resources. In India, the agricultural sector alone sustains the livelihood of around of 70% of the population and contributes nearly 35% of the net national product. Increasing agricultural productivity has been the main concern, since the scope for increasing area under agriculture is rather limited. This demands judicious and optimal management of both land and water resources. Hence comprehensive and reliable information on land use and cover, forest area soils, geological information, extent of wastelands, agricultural crops, water resources (both surface and underground) and hazards of natural calamities like drought and floods are required. Remote sensing systems, having capability of providing regular, synoptic multi temporal and multi spectral coverage of the country, play an important role in providing such information. A large number of experiments have been carried out in developing techniques for extracting agricultural related information from ground borne, air borne and space borne data. Some of the broad agricultural application areas are: