Awards & Nominations
Rosette has received the following awards and nominations. Way to go!
A New Perspective
Cvoid-19 Impact Finder
Summary
Due to Covid-19 pandemic, changes in human activity greatly affected natural environment. We want to look for different kinds of changes that are occurring in local natural habitat. We use NASA earth data to analyze changes in natural environment between 2020 and previous years. We found 5 most visible changes that were relevant to Covid-19 impacts on human activity and nature. Then, we propose to build an online application with which users can easily search through each category of data.
How We Addressed This Challenge
Our goal is to find changes in local natural environment in Africa due to Covid-19. Because huge population relies on farming and logging in Africa, so decrease in human activity can affect the local natural habitat directly. We thought that selecting and offering the right dataset for the local scientists to help them identify any significant changes happening around their local nature would help them continue their research without any local on-site observation. We searched for different kinds of data, and selected 5 different categories of data from Nasa’s earth dataset. After going over the many comparisons between each year, we found out that satellite images from 2017 March 15th are most clean and visible, so all of the data for comparison with March 15th 2020 data after Covid-19 is compared with ones on March 15th, 2017.
How We Developed This Project
We always believe that everyone should benefit from the readily available data and prepare for unpredictable future especially in times like Covid-19 crisis. However, the amount of data from NASA is too big to be utilized without prior knowledge about the topic. Therefore, we decide to build an app that provides users with processed and filtered data directly related to their chosen topic.
We used NASA WorldView, Earth Data, Giovanni to read and download the data. Then, we processed data with Panoply. We tried to incorporate Python and R, but we had difficulty using those programs to analyze the data, so we decided to just stick with Panoply and NASA WORLDVIEW. LP DAAC tutorial also was a great help in learning how to convert hdf format files and where to find resources during the challenge. With help from all these resources, we could successfully analyze each of five different categories of data.
First, we could find a significant decrease in Final Aerosol Single Scattering Albedo at 500nm in 2020 compared to 2017 on the same day. Especially in northern and southern part of Africa, there were no visibilities of Aerosol on the satellite images.
Second, Land-surface Temperature shows a slight change from Africa. Specifically, in Western Africa, we could see the temperature decreased near Kenya. Madagascar’s land temperature is abnormally high compared to 2017, but this was due to wildfire in the south.
Third, number of cases of thermal anomaly varies among different regions in Africa, but overall numbers of cases decreased. The fire radiative power in 2017 is a lot higher than 2020’s. However, in middle Africa, the fire anomaly index is concentrated in Congo compared to 2017.
Fourth, total aerosol distribution of higher level of angstrom parameter [470-870nm] is greatly decreased in southern Africa in 2020. It means that there is less fine air particle which are usually produced by smoke from car and industrial activities in the region.
Fifth, the Global daily 9km Net Ecosystem Exchange(mean) is decreased in 2020 compared to 2017 which means that there are more amount of carbon produced by heterotrophic respiration in this year. This can be related to increase in wildlife activity as well as less amount of net primary production due to less carbon output in local environment.
Even though, all of the members were in different local time zone, we managed to work nonstop. When it’s night time for some members, it’s morning for the other, so we handed over the work to each other before going to sleep. It was still difficult to keep connected to some members when there was an internet problem. Nonetheless, we were really happy to get together online and finish our journey successfully.
Please Find a presentation of the project here:
Login: https://twitter.com/abir_arsalane/status/1267195215959527429?s=20
Category: https://twitter.com/abir_arsalane/status/1267215283107831811?s=20
Information: https://twitter.com/abir_arsalane/status/1267225991237206018?s=20
Project Demo
As our challenge is about possible changes in natural environment due to Covid-19, we propose our app to include specifically 5 categories which are
1. Final Aerosol Single Scattering Albedo at 500nm
2. Land-surface Temperature
3. Thermal Anomaly
4. Total Aerosol Distribution of Higher Level of Angstrom Parameter [470-870nm]
5. Global Daily 9km Net Ecosystem Exchange(mean)
For each category, we use NASA open API and near real-time satellite data to provide users with latest as well as largest dataset. In this way, not only professionals but also citizens with no scientific background can get access to the data and educate themselves with changes occurring in natural environments.
Research Dataset and Demonstration of Solution can be found here:
https://afifibytes.github.io/rosette/
Data & Resources
Data:
43,396,342 MYD09GA.A2020089.h22v08.006.2020091024259.hdf
44,134,105 MYD09GA.A2020090.h21v07.006.2020098212621.hdf
40,765,785 MYD09GA.A2020090.h21v08.006.2020098213612.hdf
73,084,108 MYD09GA.A2020090.h22v07.006.2020098213306.hdf
73,441,782 MYD09GA.A2020090.h22v08.006.2020098213448.hdf
75,859,841 MYD11C3.A2017060.006.2017094160714.hdf
76,370,579 MYD11C3.A2020061.006.2020099122015.hdf
514,119 MYD14.A2017089.1105.006.2017090144323 (1).hdf
514,119 MYD14.A2017089.1105.006.2017090144323.hdf
260,073 MYD14.A2017089.2320.006.2017090154934 (1).hdf
260,073 MYD14.A2017089.2320.006.2017090154934.hdf
481,400 MYD14.A2020089.1110.006.2020090111708.hdf
234,872 MYD14.A2020089.2325.006.2020090131811.hdf
524,444 MYD14.A2020090.1150.006.2020091114045.hdf
356,378 MYD14.A2020090.1155.006.2020091114036.hdf
714,614 OMI-Aura_L3-OMAERUVd_2017m0329_v003-2017m0821t151748.he5
264,708 OMI-Aura_L3-OMAERUVd_2019m0430_v003-2019m0822t153033.he5.ncml (1).nc
264,708 OMI-Aura_L3-OMAERUVd_2019m0430_v003-2019m0822t153033.he5.ncml.nc
264,636 OMI-Aura_L3-OMAERUVd_2019m0502_v003-2019m0822t153309.he5.ncml.nc
659,820 OMI-Aura_L3-OMAERUVd_2020m0329_v003-2020m0402t221123.he5
139,188,833 SMAP_L4_C_mdl_20170315T000000_Vv4040_001.h5
137,380,833 SMAP_L4_C_mdl_20190115T000000_Vv4040_001.h5
138,269,343 SMAP_L4_C_mdl_20190215T000000_Vv4040_001.h5
139,379,645 SMAP_L4_C_mdl_20190315T000000_Vv4040_001.h5
139,888,049 SMAP_L4_C_mdl_20190415T000000_Vv4040_001.h5
141,165,602 SMAP_L4_C_mdl_20190515T000000_Vv4040_001.h5
141,726,726 SMAP_L4_C_mdl_20190615T000000_Vv4040_001.h5
141,494,328 SMAP_L4_C_mdl_20190715T000000_Vv4040_001.h5
141,608,950 SMAP_L4_C_mdl_20190815T000000_Vv4040_001.h5
141,656,844 SMAP_L4_C_mdl_20190915T000000_Vv4040_001.h5
141,321,039 SMAP_L4_C_mdl_20191015T000000_Vv4040_001.h5
139,201,091 SMAP_L4_C_mdl_20191115T000000_Vv4040_001.h5
138,020,881 SMAP_L4_C_mdl_20191215T000000_Vv4040_001.h5
137,743,626 SMAP_L4_C_mdl_20200115T000000_Vv4040_001.h5
138,334,256 SMAP_L4_C_mdl_20200215T000000_Vv4040_001.h5
139,329,125 SMAP_L4_C_mdl_20200315T000000_Vv4040_001.h5
140,169,224 SMAP_L4_C_mdl_20200415T000000_Vv4040_001.h5
141,087,119 SMAP_L4_C_mdl_20200515T000000_Vv4040_001.h5
Resources:
JAXA Satellite Monitoring for Environmental Studies,
NASA World View
NASA LP DAAC
Giovanni
NASA EarthData Search