Open nikhilchaurasia1993 opened 7 years ago
parthkhare
commented
7 years ago Hi,
0.004166667 refers to the spatial resolution of pixel in degree decimal units. In other words, satellite imagery is essentially photograph composed of pixels, 0.004166667*0.004166667 implies the size dimension of each pixel square. The conversion factor is 0.00833 degrees ~ 1km therefore 0.004166 implies 500m, or in other words 0.004166667 0.004166667 is a 500X500m grid/pixel.
nikhilchaurasia1993
commented
7 years ago Hi Parth,
Thank you. That was very helpful. I would really appreciate it if you provide your thoughts on the following:
I was analyzing the VIIRS data for a time period between 2012-2015. I noticed that the radiance values for the year 2015 show a spike in approximately 60% of the states in the US when compared to the radiance values of year
As per my understanding, owing to the economic development and population growth, the radiance from any area should increase year over year. I am not able to figure out the reason for the same.
Please let me your thoughts on this.
Thanks and regards, Nikhil Chaurasia
On Fri, Nov 25, 2016 at 12:41 PM, Parth notifications@github.com wrote:
Hi,
0.004166667 refers to the spatial resolution of pixel in degree decimal units. In other words, satellite imagery is essentially photograph composed of pixels, 0.004166667*0.004166667 implies the size dimension of each pixel square. The conversion factor is 0.00833 degrees ~ 1km therefore 0.004166 implies 500m, or in other words 0.004166667 0.004166667 is a 500X500m grid/pixel.
— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/parthkhare/NightLights/issues/1#issuecomment-262893783, or mute the thread https://github.com/notifications/unsubscribe-auth/AWLjB8DEZjKD8pT04RSSe7QlkPbngBoDks5rBoo2gaJpZM4K5QuT .
nikhilchaurasia1993
commented
7 years ago Hi Parth,
Thank you. That was very helpful. I would really appreciate it if you provide your thoughts on the following:
I was analyzing the VIIRS data for a time period between 2012-2015. I noticed that the radiance values for the year 2014 show a spike in approximately 60% of the states in the US when compared to the radiance values over 2012-15. These values are even more than the year 2016.
As per my understanding, owing to the economic development and population growth, the radiance from any area should increase year over year. I am not able to figure out the reason for the same.
Please let me your thoughts on this.
Thanks and regards, Nikhil Chaurasia
On Fri, Nov 25, 2016 at 12:41 PM, Parth notifications@github.com wrote:
Hi,
0.004166667 refers to the spatial resolution of pixel in degree decimal units. In other words, satellite imagery is essentially photograph composed of pixels, 0.004166667*0.004166667 implies the size dimension of each pixel square. The conversion factor is 0.00833 degrees ~ 1km therefore 0.004166 implies 500m, or in other words 0.004166667 0.004166667 is a 500X500m grid/pixel.
— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/parthkhare/NightLights/issues/1#issuecomment-262893783, or mute the thread https://github.com/notifications/unsubscribe-auth/AWLjB8DEZjKD8pT04RSSe7QlkPbngBoDks5rBoo2gaJpZM4K5QuT .
parthkhare
commented
7 years ago Your most welcome Nikhil,
Are working with VIIRS, if yes then is it stable (cloud free) band that you're using for this ?
On Mon, Nov 28, 2016 at 4:59 PM, Nikhil Chaurasia notifications@github.com wrote:
Hi Parth,
Thank you. That was very helpful. I would really appreciate it if you provide your thoughts on the following:
I was analyzing the VIIRS data for a time period between 2012-2015. I noticed that the radiance values for the year 2015 show a spike in approximately 60% of the states in the US when compared to the radiance values of year
As per my understanding, owing to the economic development and population growth, the radiance from any area should increase year over year. I am not able to figure out the reason for the same.
Please let me your thoughts on this.
Thanks and regards, Nikhil Chaurasia
On Fri, Nov 25, 2016 at 12:41 PM, Parth notifications@github.com wrote:
Hi,
0.004166667 refers to the spatial resolution of pixel in degree decimal units. In other words, satellite imagery is essentially photograph composed of pixels, 0.004166667*0.004166667 implies the size dimension of each pixel square. The conversion factor is 0.00833 degrees ~ 1km therefore 0.004166 implies 500m, or in other words 0.004166667 0.004166667 is a 500X500m grid/pixel.
— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/parthkhare/NightLights/issues/ 1#issuecomment-262893783, or mute the thread https://github.com/notifications/unsubscribe-auth/ AWLjB8DEZjKD8pT04RSSe7QlkPbngBoDks5rBoo2gaJpZM4K5QuT .
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--
Regards,
Parth Khare | Data Scientist | Mobile: +91 9868485655 *|Photo-stream: *https://www.flickr.com/photos/112535056@N08/ https://www.flickr.com/photos/112535056@N08/
nikhilchaurasia1993
commented
7 years ago Hi Parth,
I am using VIIRS cloud free monthly composites. Images are taken from the following data source:
http://ngdc.noaa.gov/eog/viirs/download_monthly.html
Thanks and regards, Nikhil Chaurasia
On Mon, Nov 28, 2016 at 7:27 PM, Parth notifications@github.com wrote:
Your most welcome Nikhil,
Are working with VIIRS, if yes then is it stable (cloud free) band that you're using for this ?
On Mon, Nov 28, 2016 at 4:59 PM, Nikhil Chaurasia < notifications@github.com> wrote:
Hi Parth,
Thank you. That was very helpful. I would really appreciate it if you provide your thoughts on the following:
I was analyzing the VIIRS data for a time period between 2012-2015. I noticed that the radiance values for the year 2015 show a spike in approximately 60% of the states in the US when compared to the radiance values of year
As per my understanding, owing to the economic development and population growth, the radiance from any area should increase year over year. I am not able to figure out the reason for the same.
Please let me your thoughts on this.
Thanks and regards, Nikhil Chaurasia
On Fri, Nov 25, 2016 at 12:41 PM, Parth notifications@github.com wrote:
Hi,
0.004166667 refers to the spatial resolution of pixel in degree decimal units. In other words, satellite imagery is essentially photograph composed of pixels, 0.004166667*0.004166667 implies the size dimension of each pixel square. The conversion factor is 0.00833 degrees ~ 1km therefore 0.004166 implies 500m, or in other words 0.004166667 0.004166667 is a 500X500m grid/pixel.
— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/parthkhare/NightLights/issues/ 1#issuecomment-262893783, or mute the thread https://github.com/notifications/unsubscribe-auth/ AWLjB8DEZjKD8pT04RSSe7QlkPbngBoDks5rBoo2gaJpZM4K5QuT .
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--
Regards,
Parth Khare | Data Scientist | Mobile: +91 9868485655 *|Photo-stream: *https://www.flickr.com/photos/112535056@N08/ https://www.flickr.com/photos/112535056@N08/
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parthkhare
commented
7 years ago Hi Nikhil,
There is substantial variance in the monthly data. An issue which I have been working on myself, though some of deviances can be inferred due to seasonal changes and particular events, I guess with 2016 data till November, we can have more clarity.
PS: For absolute deviation across 2014 and 2015 you can refer to the following https://www.rpubs.com/parthakhare/viirsind, let me know if this relates.
On Mon, Nov 28, 2016 at 8:11 PM, Nikhil Chaurasia notifications@github.com wrote:
Hi Parth,
I am using VIIRS cloud free monthly composites. Images are taken from the following data source:
http://ngdc.noaa.gov/eog/viirs/download_monthly.html
Thanks and regards, Nikhil Chaurasia
On Mon, Nov 28, 2016 at 7:27 PM, Parth notifications@github.com wrote:
Your most welcome Nikhil,
Are working with VIIRS, if yes then is it stable (cloud free) band that you're using for this ?
On Mon, Nov 28, 2016 at 4:59 PM, Nikhil Chaurasia < notifications@github.com> wrote:
Hi Parth,
Thank you. That was very helpful. I would really appreciate it if you provide your thoughts on the following:
I was analyzing the VIIRS data for a time period between 2012-2015. I noticed that the radiance values for the year 2015 show a spike in approximately 60% of the states in the US when compared to the radiance values of year
As per my understanding, owing to the economic development and population growth, the radiance from any area should increase year over year. I am not able to figure out the reason for the same.
Please let me your thoughts on this.
Thanks and regards, Nikhil Chaurasia
On Fri, Nov 25, 2016 at 12:41 PM, Parth notifications@github.com wrote:
Hi,
0.004166667 refers to the spatial resolution of pixel in degree decimal units. In other words, satellite imagery is essentially photograph composed of pixels, 0.004166667*0.004166667 implies the size dimension of each pixel square. The conversion factor is 0.00833 degrees ~ 1km therefore 0.004166 implies 500m, or in other words 0.004166667 0.004166667 is a 500X500m grid/pixel.
— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/parthkhare/NightLights/issues/ 1#issuecomment-262893783, or mute the thread https://github.com/notifications/unsubscribe-auth/ AWLjB8DEZjKD8pT04RSSe7QlkPbngBoDks5rBoo2gaJpZM4K5QuT .
— You are receiving this because you commented. Reply to this email directly, view it on GitHub https://github.com/parthkhare/NightLights/issues/ 1#issuecomment-263248292, or mute the thread https://github.com/notifications/unsubscribe-auth/AF- WTxxMafSJSDri71VNn2cu0HSatTsSks5rCrsGgaJpZM4K5QuT .
--
Regards,
Parth Khare | Data Scientist | Mobile: +91 9868485655 *|Photo-stream: *https://www.flickr.com/photos/112535056@N08/ https://www.flickr.com/photos/112535056@N08/
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--
Regards,
Parth Khare | Data Scientist | Mobile: +91 9868485655 *|Photo-stream: *https://www.flickr.com/photos/112535056@N08/ https://www.flickr.com/photos/112535056@N08/
nikhilchaurasia1993
commented
7 years ago Hi Parth,
Thank you. That was very helpful indeed. I may trouble you later with any other issues that i face. Thank you for your valuable time.
Thanks and regards, Nikhil Chaurasia
On Tue, Nov 29, 2016 at 10:46 AM, Parth notifications@github.com wrote:
Hi Nikhil,
There is substantial variance in the monthly data. An issue which I have been working on myself, though some of deviances can be inferred due to seasonal changes and particular events, I guess with 2016 data till November, we can have more clarity.
PS: For absolute deviation across 2014 and 2015 you can refer to the following https://www.rpubs.com/parthakhare/viirsind, let me know if this relates.
On Mon, Nov 28, 2016 at 8:11 PM, Nikhil Chaurasia < notifications@github.com>
wrote:
Hi Parth,
I am using VIIRS cloud free monthly composites. Images are taken from the following data source:
http://ngdc.noaa.gov/eog/viirs/download_monthly.html
Thanks and regards, Nikhil Chaurasia
On Mon, Nov 28, 2016 at 7:27 PM, Parth notifications@github.com wrote:
Your most welcome Nikhil,
Are working with VIIRS, if yes then is it stable (cloud free) band that you're using for this ?
On Mon, Nov 28, 2016 at 4:59 PM, Nikhil Chaurasia < notifications@github.com> wrote:
Hi Parth,
Thank you. That was very helpful. I would really appreciate it if you provide your thoughts on the following:
I was analyzing the VIIRS data for a time period between 2012-2015. I noticed that the radiance values for the year 2015 show a spike in approximately 60% of the states in the US when compared to the radiance values of year
As per my understanding, owing to the economic development and population growth, the radiance from any area should increase year over year. I am not able to figure out the reason for the same.
Please let me your thoughts on this.
Thanks and regards, Nikhil Chaurasia
On Fri, Nov 25, 2016 at 12:41 PM, Parth notifications@github.com wrote:
Hi,
0.004166667 refers to the spatial resolution of pixel in degree decimal units. In other words, satellite imagery is essentially photograph composed of pixels, 0.004166667*0.004166667 implies the size dimension of each pixel square. The conversion factor is 0.00833 degrees ~ 1km therefore 0.004166 implies 500m, or in other words 0.004166667 0.004166667 is a 500X500m grid/pixel.
— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/parthkhare/NightLights/issues/ 1#issuecomment-262893783, or mute the thread https://github.com/notifications/unsubscribe-auth/ AWLjB8DEZjKD8pT04RSSe7QlkPbngBoDks5rBoo2gaJpZM4K5QuT .
— You are receiving this because you commented. Reply to this email directly, view it on GitHub https://github.com/parthkhare/NightLights/issues/ 1#issuecomment-263248292, or mute the thread https://github.com/notifications/unsubscribe-auth/AF- WTxxMafSJSDri71VNn2cu0HSatTsSks5rCrsGgaJpZM4K5QuT .
--
Regards,
Parth Khare | Data Scientist | Mobile: +91 9868485655 *|Photo-stream: *https://www.flickr.com/photos/112535056@N08/ https://www.flickr.com/photos/112535056@N08/
— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/parthkhare/NightLights/issues/ 1#issuecomment-263277318, or mute the thread https://github.com/notifications/unsubscribe-auth/ AWLjBxsMzDU4p7ZfvP8KNwuCy6GgDHfyks5rCt3fgaJpZM4K5QuT .
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.
--
Regards,
Parth Khare | Data Scientist | Mobile: +91 9868485655 *|Photo-stream: *https://www.flickr.com/photos/112535056@N08/ https://www.flickr.com/photos/112535056@N08/
— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/parthkhare/NightLights/issues/1#issuecomment-263478702, or mute the thread https://github.com/notifications/unsubscribe-auth/AWLjB9Ip4VNWE05xqnk1vfJJ5aJN8x0Dks5rC7UvgaJpZM4K5QuT .
nikhilchaurasia1993
commented
7 years ago Hi Parth,
We are trying to get the data at a Zip level. However we are facing a few issues. Our cluster nodes are linux and we are unable to get RGDAL to work on these nodes.
Is there any other R package that you know of which can also perform operations on similar objects.? Your thoughts are highly appreciated.
Thanks and Regards Nikhil Chaurasia
On Tue, Nov 29, 2016 at 8:05 PM, nikhil chaurasia < nikhilchaurasia93@gmail.com> wrote:
Hi Parth,
Thank you. That was very helpful indeed. I may trouble you later with any other issues that i face. Thank you for your valuable time.
Thanks and regards, Nikhil Chaurasia
On Tue, Nov 29, 2016 at 10:46 AM, Parth notifications@github.com wrote:
Hi Nikhil,
There is substantial variance in the monthly data. An issue which I have been working on myself, though some of deviances can be inferred due to seasonal changes and particular events, I guess with 2016 data till November, we can have more clarity.
PS: For absolute deviation across 2014 and 2015 you can refer to the following https://www.rpubs.com/parthakhare/viirsind, let me know if this relates.
On Mon, Nov 28, 2016 at 8:11 PM, Nikhil Chaurasia < notifications@github.com>
wrote:
Hi Parth,
I am using VIIRS cloud free monthly composites. Images are taken from the following data source:
http://ngdc.noaa.gov/eog/viirs/download_monthly.html
Thanks and regards, Nikhil Chaurasia
On Mon, Nov 28, 2016 at 7:27 PM, Parth notifications@github.com wrote:
Your most welcome Nikhil,
Are working with VIIRS, if yes then is it stable (cloud free) band that you're using for this ?
On Mon, Nov 28, 2016 at 4:59 PM, Nikhil Chaurasia < notifications@github.com> wrote:
Hi Parth,
Thank you. That was very helpful. I would really appreciate it if you provide your thoughts on the following:
I was analyzing the VIIRS data for a time period between 2012-2015. I noticed that the radiance values for the year 2015 show a spike in approximately 60% of the states in the US when compared to the radiance values of year
As per my understanding, owing to the economic development and population growth, the radiance from any area should increase year over year. I am not able to figure out the reason for the same.
Please let me your thoughts on this.
Thanks and regards, Nikhil Chaurasia
On Fri, Nov 25, 2016 at 12:41 PM, Parth notifications@github.com wrote:
Hi,
0.004166667 refers to the spatial resolution of pixel in degree decimal units. In other words, satellite imagery is essentially photograph composed of pixels, 0.004166667*0.004166667 implies the size dimension of each pixel square. The conversion factor is 0.00833 degrees ~ 1km therefore 0.004166 implies 500m, or in other words 0.004166667 0.004166667 is a 500X500m grid/pixel.
— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/parthkhare/NightLights/issues/ 1#issuecomment-262893783, or mute the thread https://github.com/notifications/unsubscribe-auth/ AWLjB8DEZjKD8pT04RSSe7QlkPbngBoDks5rBoo2gaJpZM4K5QuT .
— You are receiving this because you commented. Reply to this email directly, view it on GitHub https://github.com/parthkhare/NightLights/issues/ 1#issuecomment-263248292, or mute the thread https://github.com/notifications/unsubscribe-auth/AF- WTxxMafSJSDri71VNn2cu0HSatTsSks5rCrsGgaJpZM4K5QuT .
--
Regards,
Parth Khare | Data Scientist | Mobile: +91 9868485655 *|Photo-stream: *https://www.flickr.com/photos/112535056@N08/ https://www.flickr.com/photos/112535056@N08/
— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/parthkhare/NightLights/issues/ 1#issuecomment-263277318, or mute the thread https://github.com/notifications/unsubscribe-auth/ AWLjBxsMzDU4p7ZfvP8KNwuCy6GgDHfyks5rCt3fgaJpZM4K5QuT .
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.
--
Regards,
Parth Khare | Data Scientist | Mobile: +91 9868485655 *|Photo-stream: *https://www.flickr.com/photos/112535056@N08/ https://www.flickr.com/photos/112535056@N08/
— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/parthkhare/NightLights/issues/1#issuecomment-263478702, or mute the thread https://github.com/notifications/unsubscribe-auth/AWLjB9Ip4VNWE05xqnk1vfJJ5aJN8x0Dks5rC7UvgaJpZM4K5QuT .
nikhilchaurasia1993
commented
7 years ago Hi Parth,
Can you explain the pressence of negative and zero values in the data? How do you treat these? Also, what is the best way to aggregate the data at a state leve? Do you take average or sum of the luminosity?
Thanks in advance.
Thanks and Regards Nikhil Chaurasia
On Wed, Nov 30, 2016 at 3:22 PM, nikhil chaurasia < nikhilchaurasia93@gmail.com> wrote:
Hi Parth,
We are trying to get the data at a Zip level. However we are facing a few issues. Our cluster nodes are linux and we are unable to get RGDAL to work on these nodes.
Is there any other R package that you know of which can also perform operations on similar objects.? Your thoughts are highly appreciated.
Thanks and Regards Nikhil Chaurasia
On Tue, Nov 29, 2016 at 8:05 PM, nikhil chaurasia < nikhilchaurasia93@gmail.com> wrote:
Hi Parth,
Thank you. That was very helpful indeed. I may trouble you later with any other issues that i face. Thank you for your valuable time.
Thanks and regards, Nikhil Chaurasia
On Tue, Nov 29, 2016 at 10:46 AM, Parth notifications@github.com wrote:
Hi Nikhil,
There is substantial variance in the monthly data. An issue which I have been working on myself, though some of deviances can be inferred due to seasonal changes and particular events, I guess with 2016 data till November, we can have more clarity.
PS: For absolute deviation across 2014 and 2015 you can refer to the following https://www.rpubs.com/parthakhare/viirsind, let me know if this relates.
On Mon, Nov 28, 2016 at 8:11 PM, Nikhil Chaurasia < notifications@github.com>
wrote:
Hi Parth,
I am using VIIRS cloud free monthly composites. Images are taken from the following data source:
http://ngdc.noaa.gov/eog/viirs/download_monthly.html
Thanks and regards, Nikhil Chaurasia
On Mon, Nov 28, 2016 at 7:27 PM, Parth notifications@github.com wrote:
Your most welcome Nikhil,
Are working with VIIRS, if yes then is it stable (cloud free) band that you're using for this ?
On Mon, Nov 28, 2016 at 4:59 PM, Nikhil Chaurasia < notifications@github.com> wrote:
Hi Parth,
Thank you. That was very helpful. I would really appreciate it if you provide your thoughts on the following:
I was analyzing the VIIRS data for a time period between 2012-2015. I noticed that the radiance values for the year 2015 show a spike in approximately 60% of the states in the US when compared to the radiance values of year
As per my understanding, owing to the economic development and population growth, the radiance from any area should increase year over year. I am not able to figure out the reason for the same.
Please let me your thoughts on this.
Thanks and regards, Nikhil Chaurasia
On Fri, Nov 25, 2016 at 12:41 PM, Parth notifications@github.com wrote:
Hi,
0.004166667 refers to the spatial resolution of pixel in degree decimal units. In other words, satellite imagery is essentially photograph composed of pixels, 0.004166667*0.004166667 implies the size dimension of each pixel square. The conversion factor is 0.00833 degrees ~ 1km therefore 0.004166 implies 500m, or in other words 0.004166667 0.004166667 is a 500X500m grid/pixel.
— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/parthkhare/NightLights/issues/ 1#issuecomment-262893783, or mute the thread https://github.com/notifications/unsubscribe-auth/ AWLjB8DEZjKD8pT04RSSe7QlkPbngBoDks5rBoo2gaJpZM4K5QuT .
— You are receiving this because you commented. Reply to this email directly, view it on GitHub https://github.com/parthkhare/NightLights/issues/ 1#issuecomment-263248292, or mute the thread https://github.com/notifications/unsubscribe-auth/AF- WTxxMafSJSDri71VNn2cu0HSatTsSks5rCrsGgaJpZM4K5QuT .
--
Regards,
Parth Khare | Data Scientist | Mobile: +91 9868485655 *|Photo-stream: *https://www.flickr.com/photos/112535056@N08/ https://www.flickr.com/photos/112535056@N08/
— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/parthkhare/NightLights/issues/ 1#issuecomment-263277318, or mute the thread https://github.com/notifications/unsubscribe-auth/ AWLjBxsMzDU4p7ZfvP8KNwuCy6GgDHfyks5rCt3fgaJpZM4K5QuT .
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.
--
Regards,
Parth Khare | Data Scientist | Mobile: +91 9868485655 *|Photo-stream: *https://www.flickr.com/photos/112535056@N08/ https://www.flickr.com/photos/112535056@N08/
— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/parthkhare/NightLights/issues/1#issuecomment-263478702, or mute the thread https://github.com/notifications/unsubscribe-auth/AWLjB9Ip4VNWE05xqnk1vfJJ5aJN8x0Dks5rC7UvgaJpZM4K5QuT .
parthkhare
commented
7 years ago Hi Nikhil,
When you compress the nightlights VIIRS/DMSP zip you will eventually find a raster/image/tiff file. R easily reads this file through: ras <- raster("/../viirs.tif) syntax
On Wed, Nov 30, 2016 at 3:22 PM, Nikhil Chaurasia notifications@github.com wrote:
Hi Parth,
We are trying to get the data at a Zip level. However we are facing a few issues. Our cluster nodes are linux and we are unable to get RGDAL to work on these nodes.
Is there any other R package that you know of which can also perform operations on similar objects.? Your thoughts are highly appreciated.
Thanks and Regards Nikhil Chaurasia
On Tue, Nov 29, 2016 at 8:05 PM, nikhil chaurasia < nikhilchaurasia93@gmail.com> wrote:
Hi Parth,
Thank you. That was very helpful indeed. I may trouble you later with any other issues that i face. Thank you for your valuable time.
Thanks and regards, Nikhil Chaurasia
On Tue, Nov 29, 2016 at 10:46 AM, Parth notifications@github.com wrote:
Hi Nikhil,
There is substantial variance in the monthly data. An issue which I have been working on myself, though some of deviances can be inferred due to seasonal changes and particular events, I guess with 2016 data till November, we can have more clarity.
PS: For absolute deviation across 2014 and 2015 you can refer to the following https://www.rpubs.com/parthakhare/viirsind, let me know if this relates.
On Mon, Nov 28, 2016 at 8:11 PM, Nikhil Chaurasia < notifications@github.com>
wrote:
Hi Parth,
I am using VIIRS cloud free monthly composites. Images are taken from the following data source:
http://ngdc.noaa.gov/eog/viirs/download_monthly.html
Thanks and regards, Nikhil Chaurasia
On Mon, Nov 28, 2016 at 7:27 PM, Parth notifications@github.com wrote:
Your most welcome Nikhil,
Are working with VIIRS, if yes then is it stable (cloud free) band that you're using for this ?
On Mon, Nov 28, 2016 at 4:59 PM, Nikhil Chaurasia < notifications@github.com> wrote:
Hi Parth,
Thank you. That was very helpful. I would really appreciate it if you provide your thoughts on the following:
I was analyzing the VIIRS data for a time period between 2012-2015. I noticed that the radiance values for the year 2015 show a spike in approximately 60% of the states in the US when compared to the radiance values of year
As per my understanding, owing to the economic development and population growth, the radiance from any area should increase year over year. I am not able to figure out the reason for the same.
Please let me your thoughts on this.
Thanks and regards, Nikhil Chaurasia
On Fri, Nov 25, 2016 at 12:41 PM, Parth <notifications@github.com
wrote:
Hi,
0.004166667 refers to the spatial resolution of pixel in degree decimal units. In other words, satellite imagery is essentially photograph composed of pixels, 0.004166667*0.004166667 implies the size dimension of each pixel square. The conversion factor is 0.00833 degrees ~ 1km therefore 0.004166 implies 500m, or in other words 0.004166667 0.004166667 is a 500X500m grid/pixel.
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Hi, I am new to satellite imagery. Can someone please explain what resolution means here? When i write res(ras), it returns something like: [1] 0.004166667 0.004166667 What is the meaning of this? What units are these? Is it meter/area? How should I interpret this?