Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: RADARSAT-2 SAR data re used to develop a monitoring program for Canadian forest lands with the aim to provide information on forest cutblocks and to develop algorithms for the detection of forest disturbances. Three study sites re selected in Canada and re representative of different forest types and terrain. Due to large data volumes and the need for efficiency, an automated end-to-end solution was implemented. The automated solution included image coregistration, temporal filtering, detection of forest disturbances, and delineation of the disturbances. A critical component of the overall solution was the validation: cutblock information and Landsat imagery re used. Overall there was good agreement beten the changes detected in the RADARSAT-2 data and the validation data. False positives re detected that re mainly due to changes from non-forestry natural sources and anthropogenic sources. In general, the separation of the forest and the non-forest areas-of-changes was relatively straightforward since these areas did not intersect. Further validation is planned, with data acquisition over the three study sites slated for the summer of 2016.
['Gordon Staples', 'Marco van der Kooij', 'David G. Goodenough']
I am writing a research paper on a idea Automated detection of forest disturbances using multitemporal RADARSAT-2 data
[{"from": "human", "value": "I am writing a research paper on a idea Automated detection of forest disturbances using multitemporal RADARSAT-2 data"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: RADARSAT-2 SAR data re used to develop a monitoring program for Canadian forest lands with the aim to provide information on forest cutblocks and to develop algorithms for the detection of forest disturbances. Three study sites re selected in Canada and re representative of different forest types and terrain. Due to large data volumes and the need for efficiency, an automated end-to-end solution was implemented. The automated solution included image coregistration, temporal filtering, detection of forest disturbances, and delineation of the disturbances. A critical component of the overall solution was the validation: cutblock information and Landsat imagery re used. Overall there was good agreement beten the changes detected in the RADARSAT-2 data and the validation data. False positives re detected that re mainly due to changes from non-forestry natural sources and anthropogenic sources. In general, the separation of the forest and the non-forest areas-of-changes was relatively straightforward since these areas did not intersect. Further validation is planned, with data acquisition over the three study sites slated for the summer of 2016."}]