Spatio-seasonal water presence frequency and water depth change is tried to identify in two manmade reservoirs (Massanjore dam and Tilpara barrage) over Mayurakshi river of Eastern India. These reservoirs use to supply water for hydroelectricity and irrigation services. Multi-temporal image base analysis in three phases (phase 1:1987–1999; phase 2: 2000–2006 and phase 3: 2007–2016) clearly depicted that (1) in case of Massanjore dam (67.4 km2) water presence area in pre-monsoon season is declined from 44.13 to 23.54 km2 in between phase 1 and 3. (2) In post monsoon season, same is declined from 63.37 to 37.57 km2. (3) In case of Tilpara reservoir, water presence area is declined from 3.61 to 2.20 km2 in pre monsoon season and 3.76–2.67 km2 during post monsoon season since phase 1–3. Both average and maximum NDWI scores indicating qualitative depth of water in pre and post monsoon seasons have declined over time with significant rate (R2 ranges from 0.42 to 0.58). All these indicate growing attenuation of water availability within reservoirs. This may invite hardship to the stakeholders depends on the reservoir and ecological set up of the reservoir.

The effects of climate, fertilizers and irrigation on rice yield and spatial variations of growing season climatic variability were analyzed in the three regions (North-west, Central and South-west) of Indian Punjab from 1974 to 2013. There was a linear increase in rice yield in Punjab (30 kg ha−1 year−1 in north-east, 29 kg ha−1 year−1 in central and 34 kg ha−1 year−1 in south-west region) over 40 years. The results of Mann-Kendall test and Sen’s slope estimator showed an increase in minimum temperature (0.03 °C year−1 in North-east Punjab and, 0.04 °C year−1 each in Central and South-west Punjab) but no significant trend in maximum temperature and rainfall during the rice growing season (June–September). Among different climatic and technological variables, 49% of the variance in rice yield was explained by minimum temperature. Irrigation explained 33% of the remaining 51% variance in rice yield. The larger effect of climatic variables than fertilizer and irrigation suggest that adoption of climate smart and water conservation technologies are required to reduce rice yield variability in the future and improving food security. Spatial variations in yield, rainfall and temperature across Punjab were substantial and these have important consequences for food security by indicating the need for region-specific technologies.

This study intends to evaluate the seasonal flow direction of CH4 in Northeast Asia by using GOSAT (Greenhouse Observing SATellite), in an attempt to overcome costly, laborious and time consuming ground observation which has been frequently pointed out in existing studies. It was found that the overall spatial distribution of Methane gas in Northeast Asia varies depending on the latitude, and that CH4 mainly flows southeast or east in spring, autumn and winter, but northeast or north in summer. Similar to the flow of prevailing wind and monsoons in Northeast Asia, these results show that CH4 flows mainly from the west to the east. The results also indicate that methane gas discharged from China is influencing even the Korean Peninsula and Japan.

In this study, we constructed indoor testbed to apply aerial hyper-spectral imaging sensor was to monitoring to heavy metal contaminated in soil. And a ground-based spectro-radiometer data and hyper-spectral image data were obtained for soil samples artificially contaminated with two heavy metals (Cu, Pb). Based on the comparison of spectro-radiometer and actual concentration data, specific wavelength band was classified by linear regression analysis and statistical analysis. We have established a preprocessing methodology that represents the most correlated specific wavelengths through logarithmic and derivative transformations on the reflectance data for each concentration gradient of heavy metals. Among the various methods, (Log (1/R))′ conversion was confirmed as the most effective pre-processing method for extracting specific wavelength. Then, the spectral characteristic patterns of the soil contaminated with heavy metals were confirmed through the hyper-spectral image data constructed in the indoor test bed, and spectral angle mapper which is one of the spectral characteristic matching methods was applied to confirm the classification feasibility of soil contaminated with the heavy metals.

In order to locate Astragalus appropriate areas in Salook watershed, Iran, at the first, six main effective criteria including direction, slope, altitude, temperature, rainfall and soil texture were determined based on fields study and expert experiences. Then using the analytic hierarchy process (AHP) method were weighted based on questionnaire form in the expert choice 11 software, and relative importance of each criteria and their classes were calculated. Finally, obtained maps were overlaid in ArcGIS software to determine Astragalus appropriate areas. The results showed that Northern area have higher priority than other. With the most relative importance (0.5101), the heights above 1800 m the heights above 1800 m suitable sites for Astragalus spp. The three main criteria including altitude, rainfall and temperature with the weight of 0.3043, 0.2201 and 0.1550 have the most relative importance respectively and in terms of the location are in the first to third priority. In general, from the total area of Salook watershed, 553 hectares was identified as Astragalus species suitable site. This research showed that using technology and GIS and AHP and with the least cost and time, the optimal location of medicinal plants can be determined in different lands.

Recently, location-based service have been developed and provided for living in accordance with the policy of opening public data. In addition, the use of data for solving social problems such as medical care, welfare, safety, traffic and aging is gradually spreading to various fields. Currently, a large amount of public data is analyzed to catch the current situation and develop actively various services utilizing it. However, it is focused on the study of curation method. Service technology and medium and there is very passive to use information of surrounding contexts for information utilization. And there is no systematic consideration of the relationship between different fields. In this paper, we propose a methodology to improve the value of data by networking public data related to the general or related context, as well as professional data in each field necessary for building the ultimate smart city. Especially, in order to improve the basic service infrastructure for smart city, we present the concept of smart information curation as a method to deduce the connection or association between data and to extract related elements for smart public services.

This study aims to analyze the long-term shoreline oscillations and its impact on coastal environment from a part of coastal zone of Sundarban delta over the last four decades. The present study was executed using four multi-temporal Landsat images during different dates. Automatic shoreline extraction model was developed in ERDAS Imagine software to identify the shorelines from satellite images. Digital shoreline analysis system was employed for estimation of shoreline change rate. Shoreline change analysis (erosion and accretion) study has been carried out by developing a model in ArcGIS model development tool. Transect wise shoreline change study revealed that about two third of the total transects exhibits erosion and about one third of the total transects exhibits accretion. The results of average shoreline change rate during different periods show the negative change. This study provides substantial information on the nature of shoreline changes which would assist in proper planning and management.

In this study, it was investigated the possibility of the prioritization of nine (9) sub-basins in terms of the flooding in Eskandari catchment covering an area of 1649 km2, using HEC_HMS software. In this study, after providing the information needed for flood hydrograph, SCS hydrologic simulation method was used to simulate the conversion of rainfall to runoff at sub-basin level. To implement HEC_HMS model, the annual plan was used, based on the return periods of 2, 5, 10, 50 and 100. Using the sequential removal method of the sub-basins as well as deleting the CN of each sub-basin for each stage of the implementation of the model, the flood hydrograph was calculated for each sub-basin, based on the precipitation. And therefore, the effect of each was obtained in producing the output flood. Sub-basins were prioritized in the order of their role in output flood. The results showed that the sub-basin “I “have the first priority of flooding by computing independent and dependent sub-basins. Then after, examining the independent sub-basins on the 5 and 10 yearly return period of the sub-basin “A” as well as 50 and 100 yearly return periods, the sub-basin “G” is allocated the first priority to itself.

Value added flood products helps decision makers in an efficient relief and rescue operations. On time availability of flood products, may help decision makers, in early decision making. Indian monsoon causes floods in several Indian states at a time, every year. Mapping multiple states at a time needs lot of man power and expertise. Manual flood mapping process is a time consuming process. Automatic procedures, for delineating flood and generation of value added products from satellite images can reduce the critical time-span. In the present study, an attempt is made to automate the entire flood mapping chain. The prototype study, is demonstrated for the state of Assam and the modules developed are tested for the multiple flood events during the Brahmaputra floods of August–September, 2016. The modules are checked for each stage and their outputs are validated with those as derived from manual procedures. The study has demonstrated significant reduction in the turn out time for flood response, which is very important during rapid disaster response.

Explorations and Germplasm estimation of fish biodiversity in the freshwater bodies of India are being gradually updated and analysed with a number of new discoveries though a well-defined figure of existing freshwater fish species at regional and state level remains to be calculated. The freshwater resources of India are currently experiencing an alarming decline trend in term of piscine biodiversity due to several undesired factors and consequences a considerable portion of freshwater fishes have been categorized as Threatened category. West Bengal is now becomes one of the most significant states of freshwater fish producer in India. The research study workout and divide the West Bengal state into six major physiographic divisions along with the help of modern Geoinformatics techniques (ArcGIS 10.2, Google Earth and Global Mapper software for map making purpose). The present study deals with the freshwater fish resource, distribution and biodiversity assessment of entire part of West Bengal. Occurrence of 251 fish species belonging to 15 orders, 50 families have been noted during the study period of 2012–2016. It is evident that the members belonging to Cyprinifomes constitute 37% of the total fish fauna of the river. Fluctuation in occurrence and abundance of the species are influenced by several anthropogenic activities. The demand of proper management of conservation policy is highlights through our research work.