Suchergebnisse

Most of the protected areas (PAs) in India have a hard boundary; very rarely having a transition zone to minimise the negative human wildlife interface. With increasing anthropogenic pressures, areas surrounding PAs are becoming integral for conservation. Government of India introduced a concept of Eco-sensitive Zones (ESZ) around PAs to minimise anthropogenic pressures and regulate rapid development in these areas. However, delineation of ESZs is a complex process and may take a long time. In this paper, a novel geospatial approach has been presented to delineate ESZ using a species centric approach. A case study using Swamp deer ( Rucervus duvaucelli duvaucelli ) as focal species was explored for its potential to delineate ESZ around protected area Jhilmil Jheel Conservation Reserve (JJCR) located in Uttarakhand India. Maximum entropy or Maxent model was used to identify habitat suitability. Normalised difference vegetation index (NDVI), altitude, land cover and distance to roads were used as co-variates. Seasonal variations for habitat suitability were also considered. In this study habitat suitability map of swamp deer was further rationalised based on habitat fragmentation and management limitations and proposed as ESZ of JJCR. This approach for delineation of ESZ can be very useful for PAs in India which have focal species and are yet to declare their ESZ.

Most of the protected areas (PAs) in India have a hard boundary; very rarely having a transition zone to minimise the negative human wildlife interface. With increasing anthropogenic pressures, areas surrounding PAs are becoming integral for conservation. Government of India introduced a concept of Eco-sensitive Zones (ESZ) around PAs to minimise anthropogenic pressures and regulate rapid development in these areas. However, delineation of ESZs is a complex process and may take a long time. In this paper, a novel geospatial approach has been presented to delineate ESZ using a species centric approach. A case study using Swamp deer (Rucervus duvaucelli duvaucelli) as focal species was explored for its potential to delineate ESZ around protected area Jhilmil Jheel Conservation Reserve (JJCR) located in Uttarakhand India. Maximum entropy or Maxent model was used to identify habitat suitability. Normalised difference vegetation index (NDVI), altitude, land cover and distance to roads were used as co-variates. Seasonal variations for habitat suitability were also considered. In this study habitat suitability map of swamp deer was further rationalised based on habitat fragmentation and management limitations and proposed as ESZ of JJCR. This approach for delineation of ESZ can be very useful for PAs in India which have focal species and are yet to declare their ESZ.

With as many as one third of population have become social media users exchanging information, thanks to low cost smart phones availability and social messaging platforms like Facebook, Twitter, WhatsApp, Instagram etc., TrendyInsight will play a major role on listening the public concern on local or regional issues bothering them for the government authorities to learn and prepare the remedial action. Similarly, businesses of consumer industries will be benefited from TrendyInsight for better customer services. TrendyInsight – an application software designed and developed to work in iOS platform to capture trending topics from various social networks websites based on user location and present it in graphically on map. The application utilizes the uniqueness of each social network data through Application Program Interface (API) requests based on the trend. The application eliminates the need of user login to access the public data of these social networks. The application provides other experience enhancement features like showing user's current location, updating the trending data every interval of time, searching for custom location, getting data for any custom hashtag, and settings tab to customize the type of data to be received from the social network APIs. The application was built on Swift 4 and deployment target operating system is iOS 11.

With as many as one third of population have become social media users exchanging information, thanks to low cost smart phones availability and social messaging platforms like Facebook, Twitter, WhatsApp, Instagram etc., TrendyInsight will play a major role on listening the public concern on local or regional issues bothering them for the government authorities to learn and prepare the remedial action. Similarly, businesses of consumer industries will be benefited from TrendyInsight for better customer services. TrendyInsight – an application software designed and developed to work in iOS platform to capture trending topics from various social networks websites based on user location and present it in graphically on map. The application utilizes the uniqueness of each social network data through Application Program Interface (API) requests based on the trend. The application eliminates the need of user login to access the public data of these social networks. The application provides other experience enhancement features like showing user's current location, updating the trending data every interval of time, searching for custom location, getting data for any custom hashtag, and settings tab to customize the type of data to be received from the social network APIs. The application was built on Swift 4 and deployment target operating system is iOS 11.

Citizen science has emerged as a game changer in various scientific endeavors, wherein scientific data for understanding the phenomenon could be collected by volunteers/non-specialist in a quick possible time. Citizens nowadays play an important role by functioning as "sensors" helping government/institutions by collecting and analyzing data. The advancements and convergence of technologies (Information and communication technologies (ICT)), especially the Internet and mobile technology has further assisted in such efforts. Moreover, the location sensors (GPS) and camera on board the mobile devices enables citizens to collect geotagged data. The classic example is the OpenStreetMap project where volunteers contribute towards the mapping of the planet. This paper highlights the geospatial solution based on citizen science to collect geotagged data about the water quality (turbidity). This solution is developed using open source tools and consists of an Android based mobile app and web based dashboard on the server side for real time data visualization and analysis. The web application is designed and developed using PHP, JavaScript, HTML & CSS and allows user to view the interpolated geotagged data about water quality over various background maps like OSM, Bhuvan etc. PostgreSQL/PostGIS are used as the backend geospatial data server for storing the geotagged dataset. Such solution will be very useful for water quality monitoring as part of national level project like Clean Ganga Mission using the citizen centric approach.

Citizen science has emerged as a game changer in various scientific endeavors, wherein scientific data for understanding the phenomenon could be collected by volunteers/non-specialist in a quick possible time. Citizens nowadays play an important role by functioning as "sensors" helping government/institutions by collecting and analyzing data. The advancements and convergence of technologies (Information and communication technologies (ICT)), especially the Internet and mobile technology has further assisted in such efforts. Moreover, the location sensors (GPS) and camera on board the mobile devices enables citizens to collect geotagged data. The classic example is the OpenStreetMap project where volunteers contribute towards the mapping of the planet. This paper highlights the geospatial solution based on citizen science to collect geotagged data about the water quality (turbidity). This solution is developed using open source tools and consists of an Android based mobile app and web based dashboard on the server side for real time data visualization and analysis. The web application is designed and developed using PHP, JavaScript, HTML & CSS and allows user to view the interpolated geotagged data about water quality over various background maps like OSM, Bhuvan etc. PostgreSQL/PostGIS are used as the backend geospatial data server for storing the geotagged dataset. Such solution will be very useful for water quality monitoring as part of national level project like Clean Ganga Mission using the citizen centric approach.