Ideas

First...

Tell me about you...

What are your research ideas for this course?

Outline

  • Present the Problems 
    • Disasters --> Climate Change --> Emissions
    • Small Island Developing States (SIDS)
  • Tools to monitor the problems
  • Data Sources
  • Media - Scale - Imagery
  • Dasymetric mapping
  • more ideas for projects 

Present the Problem

  • Disasters --> Climate Change --> Emissions

Disasters

Climate Change

Emissions

Positive Feedback

Disaster Cycle

DATA PREPAREDNESS
AS
DISASTER PREPAREDNESS

Tegucigalpa

Capital of Honduras

Population 850,848

landslides and flooding

 

 

Disaster and Land Use

Maps can help reduce complexity

Small Island Developing States (SIDS)

  • Environmentally vulnerable
    • coastline exposure relative to their geographic size
    • isolation from neighboring populations
    • small size of their population, high costs per capita for infrastructure and services
  • Tourism
  • Invisibility on the map

You pick a problem that interest you!

 

0
 Advanced issue found
 

Geographic Information Systems(GIS)

Data Types

 

Vector

 

Raster

Vector Data

Geographic Information Systems (GIS)

Epistemology

Positionality

Reflexivity 

and their influence

on how we process data and create visualizations 

Remote Sensing 

 

Basics of

Remote Sensing

 

Sentinel 2:

S2A (launched 23 June 2015)  and S2B (launched 7 March 2017)

Land use monitoring

True Color

Details

From Sentinel 2

Date of image: 22 Feb 2017

Spatial Resolution:

Each pixel represents 20 m

2325 columns

2960 rows of pixels

Sentinel 2

 

Active Sensor

Passive Sensor

Lidar

1 m resolution! 

Electromagnetic Energy

Features on the Earth reflect, absorb, transmit, and emit electromagnetic energy from the sun.

Properties of electromagnetic energy

Multispectral imagery 

wavelength, fequency, amplitude

The visible spectrum is small! 

What else is collected?

Bands and spectral ranges

Spectral signature

How are images rendered on our screen?

3 bands projected light  

The primary colors are Red, Green, Blue

True Color

 

 

= Band 4 Red

 

= Band 3 Green

 

= Band 2 Blue

False Color Composites

Urban areas

 

Urban=Purple​

= Band 12 SWIR II

 

= Band 11 SWIR I

 

= Band 4 Red

Vegetation

 

 

= Band 8 NIR

 

= Band 4 Blue

 

= Band 3 Red

Spectral signature

Bands and spectral signatures

Healthy vegetation

Normalized Difference Vegetation Index

NDVI=NIR-IR/NIR+IR

Classification

Supervised & Unsupervised

Animation

Animation

Slider

Sentinel-1 images track the major flooding in Kerala during the 2018 monsoon season

Slider

Land use change:

Malakal refugee camp in South Sudan

Digital Globe

Everything is spatial

Where it happened is critical to know to figure out why and how it happened

Dashboards = Power

SDG linked to Paris Agreement

International Efforts

and data

Open Data

European Environmental Agency data and links

https://ourworldindata.org/grapher/total-oda-for-water-supply-and-sanitation-by-recipient

Barriers to working with open data

https://ourworldindata.org/grapher/proportion-using-safely-managed-drinking-water

Big Data and

CyberGIS

 

Cloud Computing

  • valuable for information dissemination

  • faster and more data processing that was not previously possible

  • data access

Google Earth Engine

  • Cloud-based platform for geospatial analysis

  • Access over 40 years of satellite imagery

  • Upload own data sets to integrate with publicly available data

  • Apply range of common algorithms to data

  • Export images, tables, charts, map outputs

Hansen et al (2013)

High-Resolution Global Maps of 21st-Century Forest Cover Change, Science  

15 Nov. Vol. 342, Issue 6160, pp. 850-853 DOI: 10.1126/science.1244693.

Title Text

// Load Sentinel-2 TOA reflectance data.
var dataset = ee.ImageCollection('COPERNICUS/S2')
                  .filterDate('2018-01-01', '2018-12-30')
                  // Pre-filter to get less cloudy granules.
                  .filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE', 20))
                  

//true color
var rgbVis = {
  min: 0.0,
  max: 2500,
  bands: ['B4', 'B3', 'B2'],
};
//urban visualization
var urbanVis = {
  min: 0.0,
  max: 2500,
  bands: ['B12', 'B11', 'B4'],
};

//Agriculture visualization
var agVis = {
  min: 0.0,
  max: 2500,
  bands: ['B11', 'B8', 'B2'],
};
//Healthy vegitation visualization
var VegVis = {
  min: 0.0,
  max: 2500,
  bands: ['B8', 'B11', 'B2'],
};

//Land Water visualization
var WaterVis = {
  min: 0.0,
  max: 2500,
  bands: ['B8', 'B11', 'B4'],
};

//Utrecht
Map.setCenter(5.104480, 52.092876, 11);

//different layers 
Map.addLayer(dataset.median(), rgbVis, 'RGB');
Map.addLayer(dataset.median(), urbanVis, 'Urban');
Map.addLayer(dataset.median(), agVis, 'Agriculture');
Map.addLayer(dataset.median(), VegVis, 'Vegitation');
Map.addLayer(dataset.median(), WaterVis, 'Water');

//END

Modeling the Future

Dasymetric Map

Spatial Media  

Imagery

Scale  (Maps to VR)

Pick the problem

What is your communication Goal? 

What do you hope to find? 

What data are available?

 

Ideas

  • Story Map
  • Anything related to the SDGs
  • Covid 19 linked to biodiversity...inequity...
  • Using GEE: Measure emissions globally (or locally in India or for example) since COVID-19 to SDGS? 

Thank you!

Questions?

GSS_ideas_for_Projects_with_me

By Britta Ricker

GSS_ideas_for_Projects_with_me

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