Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-8, 787-791, 2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
28 Nov 2014
Climate Change for Agriculture, Forest Cover and 3d Urban Models
M. Kapoor1 and D. Bassir2,3 1Computer Engineering Department, Mukesh Patel School of Technology Management and Engineering, NMIMS deemed to be University, Mumbai, Maharashtra, India
2Institute of Industry Technology, Guangzhou & Chinese Academy of Sciences (IIT, GZ&CAS) Room A1005, R&D Building, Haibin Rd, Nansha District, Guangzhou, China
3Dept. GMC, Université de Technologie de Belfort-Montbéliard 90010 Belfort cedex, France
Keywords: Landsat TRIS/8/LDCM, Forest Change, Decision support, NDVI, Eclipse, 3D Urban Models Abstract. This research demonstrates the important role of the remote sensing in finding out the different parameters behind the agricultural crop change, forest cover and urban 3D models. Standalone software is developed to view and analysis the different factors effecting the change in crop productions. Open-source libraries from the Open Source Geospatial Foundation have been used for the development of the shape-file viewer. Software can be used to get the attribute information, scale, zoom in/out and pan the shapefiles. Environmental changes due to pollution and population that are increasing the urbanisation and decreasing the forest cover on the earth. Satellite imagery such as Landsat 5(1984) to Landsat TRIS/8 (2014), Landsat Data Continuity Mission (LDCM) and NDVI are used to analyse the different parameters that are effecting the agricultural crop production change and forest change. It is advisable for the development of good quality of NDVI and forest cover maps to use data collected from the same processing methods for the complete region. Management practices have been developed from the analysed data for the betterment of the crop and saving the forest cover
Conference paper (PDF, 839 KB)

Citation: Kapoor, M. and Bassir, D.: Climate Change for Agriculture, Forest Cover and 3d Urban Models, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-8, 787-791,, 2014.

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