Projects
Check out all 5 SoEE projects below.
All eligible participants have a chance of being accepted for upto 1 project per individual.
Once you pick your project, submit your project proposals here.
ATREE: Mapping the spread of invasive species in India: Lantana camara in forests and Prosopis juliflora in grasslands
Description:
India’s forests and grasslands are under threat due to the spread of invasive species, a species that is not native
and has a tendency to spread to a degree believed to cause damage to the environment, human economy or
human health. Many invasive plant species thrive because they can outcompete native vegetation in accessing
water and nutrients. Some even produce chemicals in their leaves or root systems which inhibit the growth of
other plants around them. Lantana camara and Prosopis juliflora are two such invasives that have taken over
landscapes in India.
The proposed project will
1. Map the spread of Lantana and Prosopis throughout India over the last 30 years.
2. Correlate the occurrence of these invasives with other variables (e.g. soil moisture,
temperature)
ICRISAT: Automatic Approach using Machine learning for Irrigated area mapping
Description:
Crop specific domain mapping is one critical area where ICRISAT has demonstrated successful approaches by traditional methods. Using the latest advances in Machine learning and large scale computing, Irrigated areas need to be mapped using both optical and SAR data. Training sampling data will be made available from ground truth field data.
The project for Temporal indices need to be derived using satellite spectral bands. Spectral matching techniques and supervised/unsupervised classification algorithms will be used for mapping of irrigated and non-irrigated areas.
NCF: Building an app for robust visualization of ecological status and change for select conservation sites in the Western Ghats
Description:
Biological diversity is distributed unevenly across the globe, and even within national borders. Relatively small regions--like the Western Ghats mountains of southern India--account for a disproportionately large variety of ecosystems and species. Thus, for many decades now, many sites across the Western Ghats have been set aside under different legal frameworks to promote conservation. How are these conservation sites faring over time? While many of the measurements necessary to answer this question must necessarily come from ground surveys, with the advent of earth observation and analysis platforms like Google Earth Engine, it is now possible to access, aggregate and analyse historical archives of earth observation imagery to obtain insights about the status of these conservation sites. Such insights could include status and trends in land cover and surface water, forest extent and condition, changes to agricultural landscapes, climatic anomalies, as well as data on human demography and settlement. Using available sources of such data on the Google Earth Engine platform, this project aims to put together a web-application to visualise, analyse and export such data for a set of chosen sites across the Western Ghats
WRI: Water Quality Monitoring using Sentinel 2
Description:
India’s surface water bodies have been facing water quality issues in the recent past. Since the number of ground monitoring stations are very sparse and have data gaps, it becomes a necessity to use satellite images for monitoring water quality. The project intends to model and estimate certain water quality parameters from satellite images and archival water quality measures obtained from ground stations in the Ganges basin.
Satellite data from Copernicus’ Sentinel 2 programme would be used for the project. Ground monitoring data. The study area of the project would be Ganges basin and urban water bodies in the cities of Chennai and Bengaluru.
CWS: Wild Seve - Tracing wildlife conflict in India through cropping patterns
Description:
Bandipur and Nagarahole in Karnataka are high human-wildlife conflict zones. Wild Seve is a CWS initiative to address conflict through compensation for loss of livelihoods and lives. About 95% (between 2015-19) of our cases arise from crop damage. Assessing and predicting crop patterns would be a huge step forward in predicting conflict hotspots for targeted interventions.
Reliable, large-scale agricultural mapping is hindered by complex cropping patterns and fragmented landscapes in India. To address this we will be conducting supervised classification of medium resolution satellite imagery using crop data collected through the Wild Seve initiative. Wild Seve assists families to receive compensation in the face of loss of livelihoods or lives due to human- wildlife conflict. It is a continuous monitoring program with incidental data on crops that have been damaged due to wildlife.