SpaceApes

Universal Event | Seeing the unseeable - Viewing Bugs from Space

Where Did The InsectsGO?

High-Level Project Summary

We have developed an app called InsectGo that creates awareness about the effect of ALAN (Artificial Light at Night) on insect species and gathers further data for research in this field. We correlated the spatial intensity of night time light with the distribution of insect species known to be affected by light pollution. The effect of light pollution on insects has not been studied sufficiently on a global scale, in terms of species studied as well as regions covered. Our app aims to fill the gaps in available information based on user input and use of geospatial data.

Link to Project "Demo"

https://youtu.be/camvYjQkDDI

Link to Final Project

https://insect-go-2021.glideapp.io/

Detailed Project Description

What exactly does it do?

InsectGO is an app to educate users about the effect of light pollution on insects and help them know more about individual insect species. They can also know more about how space agency data can be used to aid insect conservation.

Features of InsectGO:


Homepage: This page presents all the features of the app in a user friendly manner. This page aims to help the user to navigate through the various sections.

Explore: The app hosts an ‘Explore’ section where users can find detailed articles to help them understand the effects of light pollution and ALAN, in particular, on different insect species and the importance of insects.

We have included the case studies of effects of ALAN on fireflies and Lepidopterans, the insects that we mainly studied during the duration of the hackathon

Browse: The app has a ‘Browse’ section where the user can search insects by scientific name, common name or IUCN Red List category.

There are individual pages made for every insect species listed on the app. This page contains a demonstrative map showing the area of occurrence of the insect along with the NTL distribution of that region obtained from NASA Black Marble VNP46A2 data.

 

Users can ask their queries about different species too.

Insectagram: To promote insect observation and conservation and the general awareness towards insects, we have also included an ‘Insectagram’ section in the app.

In this section, users can post photos of insects that they have observed. We will be obtaining the date of observation and the location so the images will be geotagged and can be used to increase the database of insect population.

The photos will be displayed publicly and other users can interact with them by liking and adding comments.

About: The ‘About’ section gives additional information on the motivation and aims of this project and the members involved in it. 

The ‘About’ section also contains several more articles on specific effects of ALAN on insects.



Future plans

  • We plan to include an interactive map based User Interface for displaying effects of NTL on insects. The user will be prompted to select a polygon region on the map. On selection, the app will display the time series graphs of insect population and intensity for the user to observe and interpret. The major hurdle in this regard is the unavailability of reliable insect population data. The trends in the insect population data majorly represent the increasing trend in insect observations over the years and not the actual trends. 
  • Implement APIs to ensure the app displays the latest information to users as more species of insects are discovered and studied, as more research is done on the effect of ALAN on different insect species, and as the global NTL distribution keeps changing.
  • Further observe if the spatial distribution of some species has actually decreased over time and try to correlate it with the changing patterns of night time lighting. Present these findings as interactive maps that the user can use to observe a time series comparison of species occurrence vs NTL distribution.
  • Evaluate the biological effects of ALAN on insect species known to be affected by light pollution eg- moths, and eventually other insect species, in greater detail and present our findings in a user-friendly form in our app to communicate the information to a wider audience.
  • We plan to make ‘Insectagram’ a full-fledged citizen science project blended with some social media features for insect observers and insect lovers. The data (images, date and location) will be openly available to access. Though similar in concept to iNaturalist, our Insectagram will help to increase the public appeal of such initiatives by appealing to the social media conscious common citizens. It seeks to harness the popularity of social media platforms to create awareness about less explored fields of insect conservation. Public interest will ensure that governments fund and invest more in research in these fields. This will help scientists to use newer technology and collaborate on a bigger scale.

How does it work?

The app is made with the help of Glideapps. Glideapps is a tool that can be used to make Android or iPhone applications from Google Sheets. Google Sheets works as the database of the app. All the content of the app is stored in the Google Sheets workbook designated for the app. Each tab on the app has a specific sheet from where the app reads its content or writes to. Glideapp abstracts the front-end and back-end development process and lets developers focus on the bigger picture. 


What benefits does it have?

The app will benefit both users and researchers and most importantly, insects.


  1. Users will be able to easily access information about insects and the effects of ALAN.
  2. It will encourage researchers to innovate and experiment with new methods of insect observation.
  3. We also hope that the app will benefit insect conservationists to identify which insect species need conservation due to light pollution. It will also help them demarcate the regions where conservation efforts need to be concentrated, rather than blanket conservation, which might not be as effective. 
  4. The app will also be beneficial to teachers and students as the students can learn about the different species of insects and their regions of occurrence. They can also try to spot insects on their own and share with other insect enthusiasts through this app. 

What do you hope to achieve?

We hope to increase the awareness regarding insects and the effects of ALAN on them. Researchers come from the populace. If we can make the average person more aware of the effects of ALAN on insects, we hope that it will drive research in this field.We further hope to expand the possibilities of research in this field to include high resolution multispectral NTL data to study insect populations. We hope our initiative will drive governments to adopt better street lighting policies and make citizens adopt practices to combat light pollution. 


What tools, coding languages, hardware, or software did you use to develop your project?  

Softwares

  • Quantum Geographic Information System (QGIS) - This cartography application was majorly used to process and analyse Black Marble VNP46A1 and VNP46A2 data files. 
  • GlideApps IO - The software was used to develop an interactive application. The application comprises an insect database and provides an open ended citizen science collaboration opportunity. The application also has prospects of machine training for enhancing insect detection techniques.
  • Figma - We used the software for structuring our app before moving into final design stages on GlideApps. 
  • Google Services - The application was used to document studies and all of our documentation related to the project. 
  • Online Collaboration System - Microsoft Teams Version 1.4.00.22368 - The system was used for online collaborative activities especially meetings and regulating task timelines
  • Anaconda® Distribution including Anaconda Navigator operating Python 3.8.5 
  • Scientific Python Development Environment - Spyder (IDE) Version 4.1.5 - The software was used to analyse insect volume across regions and detection techniques over time. 

Tools

  • Geospatial Data Abstraction Library - GDAL - This library was exceptionally useful in processing HDF5 file types as extracted from NASA data sources for Suomi NPP VIIRS VNP46A1 and VNP46A2 data archives
  • Google - MyMaps Interactive Maps - The software was used to process insect data and prepare interactive mapping prototypes.

Data

  • GSFC NASA Black Marble Tile Grade Shapefile
  • NASA Level - 1 and Atmosphere Archive & Distribution System Distributed Active Archive Center (LAADS DAAC)
  • VNP46A2 - VIIRS/NPP Gap-Filled Lunar BRDF-Adjusted Nighttime Lights Daily L3 Global 500m Linear Lat Lon Grid 

Román, M.O., Wang, Z., Sun, Q., Kalb, V., Miller, S.D., Molthan, A., Schultz, L., Bell, J., Stokes, E.C., Pandey, B. and Seto, K.C., et al. (2018). NASA's Black Marble nighttime lights product suite. Remote Sensing of Environment 210, 113-143. doi:10.1016/j.rse.2018.03.017.


Use Cases of the softwares


QGIS 

  • Used QGIS to plot the data points of the insect population data obtained from GBIF over the night time light (NTL) composite GeoTIFF obtained from the Black Marble data. This was done to explore correlations between the insect population and areas of high NTL intensity. 
  • The insect population data was converted into shapefiles and KML using QGIS which can be exported into other GIS softwares or Google Earth or Google Maps for analysis/user interaction. 
  • We obtained occurrence region shapefiles of insects affected by light pollution from the IUCN website. To confirm our hypothesis that insects are affected where NTL is higher, we imported the shapefile into the QGIS, layed on top of the NTL composite from Black Marble data. There was a clear correlation observed. The insects that were affected by light pollution (as listed by IUCN) had their regions of occurrences overlapping with the regions of high NTL intensity. 



  • Further, we used QGIS similarly and tried to assess the risk to Lepidopterans. It was found that a huge number of Lepidopteran species exist in high NTL intensity regions and thus may be at risk. 



Glideapps IO


  • We used Glideapps to make an app called InsectGo. This app lets users explore species that are affected by light pollution. We have provided multiple articles on the app to make the users aware of the effects of ALAN on insects. Through the app, we have also made an attempt to document our work and observations.
  • We collaborated on Figma to create the structure of the app before starting with the actual design process. 
  • After the structure was ready, we proceeded to build the app on Glideapps. Google sheets served as the database for the app. Google Drive was used to store the images and the data. 


Google Services


  • Google Docs and Google Sheets were very helpful for collaboration on the internet as all the team members were working remotely. 
  • Google Docs was used extensively to store all kinds of resources, references and tools links. It was also used to prepare the content for the app and the project submission as multiple members were working on it. 
  • Google Docs was also used to document the entire project. 
  • Google Sheets proved very helpful in storing huge quantities of insect data that we obtained from GBIF and IUCN. Since multiple people were involved in the acquiring and processing of the data, Google Sheets helped us transfer huge quantities of data very easily. 
  • Google Sheets helped us do quick analysis of the data whenever we needed it before processing with a more detailed analysis. 
  • Google Drive helped us store and transfer large files that are required for geospatial analysis in GIS platforms. 
  • We had formed a Google Group for the team which helped in easy sharing of files and documents.


Microsoft Teams (ver 1.4.00.22368)


  • The platform was used by the team for all sorts of collaborative meetings and work distributions. We covered extensive meet hours on the platform of almost 8 hours and 4 GB of data resources shared.
  • We Channeled work distribution into 4 categories: 
  1. Content - A part of our team worked on developing the content for the application that we have produced. 
  2. Design and Prototyping - The prototyping and development of the application was covered under this section of the team.
  3. Interactive Map - Here we tried to refine and process data sources for the development of the interactive maps. The system used for these purposes was QGIS
  4. R&D - In this part of our work we researched the various scientific aspects of our project including ALAN, an insect based activities study. We studied the impact of ALAN on moths and fireflies. 
  • We processed all the HDF5 files as extracted from LAADS DAAC Black Marble Archive of Suomi NPP - VIIRS VNP46A2. And used the platform’s storage and sorting features for structuring our resources at all times. 


Python


  • We used Anaconda® Distribution including Anaconda to work on the Scientific Python (v3.8.5) Development Environment (Spyder v4.1.5). The work that we did on python was majorly a supportive framework to various activities in our project from processing timelines of insect detections to debugging conversion tool scripts we relied on python. 
  • We generated time series charts from csv files using basic pylab libraries. We also used scientific libraries like numpy and pandas
  • We used the powerful python debugger to fix errors in our scripts that we extensively used while performing cartographical operations on our GIS softwares.



Black Marble Data


  • After doing a literature study of effects of ALAN on insects and deciding on our project topic, we considered several options for NTL data. 
  • We shortlisted out of those options based on our requirements of spatial and radiometric resolution and Black Marble product VPN46A2 (Gap filled, and moon light corrected) was the best option for us. 
  • After that, we went through the Remote Sensing and Night Time Lights Backgrounders on the earthdata website. This helped us build a basic understanding of the terms and concepts related to remote sensing and NTL. 
  • We went through a pre-recorded training video on Black Marble data from ARSET. On completion of the training, we were well equipped to obtain the data from LADS DAAC and analyse the obtained data using QGIS. 

Space Agency Data

What space agency data you used in your project

We used,


  • NASA Black Marble Suomi NPP - VIIRS VNP46A2 Data Archive using the LAADS DAAC Data Archive of NASA 

Citation - Román, M.O., Wang, Z., Sun, Q., Kalb, V., Miller, S.D., Molthan, A., Schultz, L., Bell, J., Stokes, E.C., Pandey, B. and Seto, K.C., et al. (2018). NASA's Black Marble nighttime lights product suite. Remote Sensing of Environment 210, 113-143. doi:10.1016/j.rse.2018.03.017. 

Data used: HDF5 files for various years from 2012 to 2021


How you used it

  • We used the Black Marble data to generate maps using QGIS software to study how Artificial Light at Night (ALAN) has impacted the insect densities across time keeping the data as base reference in this vision. 
  • We used the insect data to plot and design time maps to analyse the variation in insect densities in various regions and their correlations with ALAN.


How it inspired your project

Black Marble data has been a great initiative by NASA. It helped us understand the change of Artificial Light at Night and how we saw the changes in insect population densities of high light intensity regions. The availability of this data has helped us immensely after having taken up this project and after completing it we all stand by our view that this data is exceptionally insightful and it holds a great potential for greenfield research projects. We believe that such data should be encouraged for research usage at all levels. 

Hackathon Journey

How would you describe your Space Apps experience?

This hackathon has been an experience of a lifetime. This was the first time we were participating in the NASA SpaceApps Challenge and undoubtedly it has been a vivid experience. From the mind boggling challenges to innovative ideas that various participants brought to the table. The deep insights that we got from the Subject Matter Experts and the dedication of our local organizers. It was equally enthralling for us to go through the world of insects and how we have over the years neglected them. We were blown away by the level of precision and variation of satellite monitoring that we have attained today.


What did you learn?

The experience of SpaceApps has been truly enriching. The new skills we learnt were:


  • Advanced Cartography using GIS softwares like QGIS
  • Effects of Artificial Light at Night (ALAN) on the biosphere
  • Effects of ALAN on insects such as Moths and Fireflies
  • Understanding the NASA Black Marble Data and how the technology has been refined over the years
  • A new Python library - GDAL
  • Developing Apps with softwares such as GlideApps and Figma


What inspired your team to choose this challenge?

When we were younger, when the halogen lights of the light posts were dimmer, the roadside trees even in urban Kolkata would be filled with pulses of small green lights going on and off. Tiny fireflies lighting them up like Christmas trees. Each firefly has a unique rhythm of glowing up, as if like a fingerprint that helps other fireflies tell Joe from Jordan. However, all the fireflies would flash in sync like the twinkling of stars in the night sky. Unfortunately, neither of them - the fireflies nor the stars are visible now thanks to one primate that was so attracted by an artificial source of light that it left no corner of the world unlit. Almost 80% of the world receives at least one of the three categories of Artificial Night at Light (ALAN). Apart from habitation loss, the rapid increase in ALAN has led to drastic declines in the population of fireflies and moths worldwide. Fireflies play a major role in the food chain - they are both predators and prey - and are essential for balance in the ecosystem. There have been local studies on the decline of fireflies and one such study has also been reported in the Oxford Journal of Bioscience. However, very few global studies have been conducted. We took up this challenge to try to fill that gap and remind people about the enchanting romance of the light of the fireflies - the light of nature, and not the light that destroys it. 


What was your approach to developing this project?

We started by reading about the various human impacts on insect populations and came to learn that habitat loss, pesticide use, invasive species, and climate change are the major forces driving a decline of insect species. Another less explored harbinger of the insect apocalypse is artificial light at night (ALAN). We decided to take this topic up and explore how ALAN affects insect species.

We obtained data on insects that have been already studied and confirmed to be affected by light pollution from the IUCN Red List of Threatened Species and plotted it on the world map to see its correlation with the presence and intensity of night time light (NTL). For the NTL data we used NASA Black Marble Suomi NPP - VIIRS VNP46A2. The superposed maps showed a clear correlation between highly lit areas and presence of threatened species, as expected.

However we noticed some gaps in these observations by analysing the map:


  1. Study of the effect of light pollution on insects was not carried out on a global scale, almost all the studied species were found to be in North America.
  2. The studied species almost exclusively belong to the Lampyridae family indicating that most research was focused on fireflies/lightning bugs and other species were not sufficiently studied for being affected by ALAN.

Though there have been no conclusive studies on the effect of light pollution on moths on a global scale , we observed some studies that explored the effect on a local scale. So we further decided to study the correlation between NTL and occurrence of Lepidopterans on a global scale by using species occurrence data on Lepidopterans and NASA Black Marble Suomi NPP - VIIRS VNP46A2.




In Europe, where Lepidopterans have been most widely studied, we observed a trend that irrespective of the Red List status of the Lepidopteran species, species diversity (indicated by the opacity of the coloured regions) was more in the areas with less ALAN and more lit areas had lower species diversity.

The global picture does not offer such a conclusive correlation but that this is due to the lack of widespread on field studies. By doing ecological modeling for moth species we seek to confirm our hypothesis that species diversity of insects is indeed affected by light pollution.

We need to further observe if the spatial distribution of some species has actually decreased over time and try to correlate it with the changing patterns of night time lighting.

Due to the large amount of data that must be analysed and our lack of resources to conduct that analysis right away, we have considered that as a future plan to evaluate the effect of ALAN on moths, and eventually other insect species, in greater detail.

Our research pressed upon us the need to create awareness about the effect of light pollution on insect species. So we decided to create an app called InsectGO. This app 


How did your team resolve setbacks and challenges?

While developing this project we faced a number of challenges and setbacks such as unavailability of data about some species, lack of studies conducted in some regions, lack of knowledge on choosing appropriate space agency datasets.

We solved the last problem by consulting the Subject Matter Specialists who resolved our doubts and explained the nuances of the available datasets and eventually we were able to use it in the desired way for our research.

Our research identified the lack of research and documentation in different parts of the world. The project we developed will hopefully make people more aware of the gaps in existing records and create interest to conduct research in unstudied regions and promote the use of space data to study insect species on a global scale.


Is there anyone you'd like to thank and why?

We would like to heartily thank NASA SpaceApps Challenge and their entire Global Organizing team for bringing this opportunity to us. We would like to extend our gratitude towards our helpful Subject Matter Experts Rupesh Shreshtha, Sara Lubkin, Space Apps Ambassador Tracey for helping us out through the challenge. We would like to thank our local lead, Reese Ingraham for making the hackathon more fun than ever, providing support at all times and being there for us. We would like to take this opportunity to present our gratitude for making SpaceApps such a gracious and welcoming place for us!

References

Data

Resources

  1. Paper on Ecological Modelling 
  2. MODIS Web Ecological Modelling of Insects
  3. Remote Sensing Data to Detect Hessian Fly Infestation in Commercial Wheat Fields | Scientific Reports
  4. A Community for Naturalists · iNaturalist
  5. GBIF.org
  6. Remote sensing of bark beetle damage in urban forests at individual tree level using a novel hyperspectral camera from UAV and aircraft
  7. What are EBVs? – GEO BON
  8. The Many Hues of London
  9. ESA - Night lights in Europe
  10. Nighttime Lights | Earthdata
  11. A new source of multi-spectral high spatial resolution night-time light imagery—JL1-3B
  12. Is light pollution driving moth population declines? A review of causal mechanisms across the life cycle
  13. Moths are strongly attracted to ultraviolet and blue radiation
  14. The impact of artificial light at night on nocturnal insects: A review and synthesis
  15. A window to the world of global insect declines: Moth biodiversity trends are complex and heterogeneous
  16. Backgrounders | Earthdata
  17. Harnessing Remote Sensing Data for Biological and Ecological Research | Earthdata
  18. Geospatial Services | Earthdata
  19. An Absolute Beginner's Guide to QGIS 3
  20. GIS Tools | Earthdata
  21. Black Marble User Guide Version 1.1
  22. How to Access LAADS Data - LAADS DAAC
  23. ARSET - Introduction to NASA’s "Black Marble" Night Lights Data
  24. https://www.smithsonianmag.com/smart-news/light-pollution-contributes-insect-apocalypse-180973642/
  25. Light pollution is a driver of insect declines
  26. Diel behavior in moths and butterflies: a synthesis of data illuminates the evolution of temporal activity - Organisms Diversity & Evolution
  27. A window to the world of global insect declines: Moth biodiversity trends are complex and heterogeneous
  28. Four ways to curb light pollution, save bugs: Insects have experienced global declines. Flipping the switch can help

Tools

Tags

#insects #seeing-the-unseeable-viewing-bugs-from-space #night-time-light #NTL #species-occurrence #NASA #NASASpaceAppsChallenge #impact

Global Judging

This project has been submitted for consideration during the Judging process.

Seeing the unseeable - Viewing Bugs from Space

Our lives hinge on the wellbeing of insects; at the same time, insect biodiversity is disproportionately affected by human actions. Your challenge is to develop innovative ways to advance our ability to detect insect life, track and predict change over time, and communicate that information to scientists and society to combat the loss of insect biodiversity.