Real-Time Crop & Drought Monitoring System – RECENT

RECENT

RECENT combines a data from Multiple Satellites Observations Monitor and Assess Impact from Drought in Regional Scale. Daily/Monthly Drought index data with Satellite Rainfall and Land Surface Temperature are available to Visualize and Download through this Web Site (http://iis.gic.ait.ac.th).

The RECENT service is available for countries; Bangladesh, Bhutan, Cambodia, China, India, Indonesia, Lao_PDR, Mongolia, Myanmar, Nepal, Pakistan, Philippines, SriLanka, Thailand & Vietnam.

Satellite observed Rainfall and Land Surface Temperature data are used here to obtain a daily drought product called Keetch-Byram Drought Index (KBDI), which ranges from 0 (wet condition) to 800 (dry condition). Anomaly of drought index (KBDI) which is deviation from long term average if Drought Index is an Indicator of Drought Condition. Hourly global rainfall data at 0.1° spatial resolution is obtained from GSMaP NRT System by Japan Aerospace Exploration Agency (JAXA). It is derived from microwave radiometers (e.g., TMI, AMSR-E and SSM/I) and infrared radiometers (e.g., MTSAT, METEOSAT and GOES). This is an hourly rainfall product which is available to public after 4 hours after the observations. Land Surface Temperature (LST) data are obtained from MTSAT, a weather satellite of the Japan Meteorological Agency (JMA) with a spatial resolution of 4 km. LST is observed in every 30 minutes using 4 thermal-infrared channels.

The service is run and managed by:

Institute of Industrial Science, University of Tokyo Japan (https://www.iis.u-tokyo.ac.jp/)

Geoinformatics Center, Asian Institute of Technology Thailand (http://www.geoinfo.ait.asian/)

Additional information

  • Drought Index KBDI (Link) (PDF) (PDF) (PDF)
  • Consistency of satellite-based precipitation products in space (PDF)
  • Product Tutorial on Land Surface Temperature (Link)
  • JAXA Global rainfall watch (Link) (PDF) (PDF) (PDF) (PDF) (PDF)
  • JAXA Global rainfall watch web tool (Link)



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Health & Air Quality – From Space

Monitoring air pollutants distribution in urban areas are critical for public health and safety. A country like Pakistan with no network of advanced weather stations to extract high quality data to derive information products is very important. Trend maps of pollutants and other information parameters derived from satellite remote sensing data is a replicable technique to integrate into management decisions. This allows city management to effectively monitor visibility and air quality concerns informing public for to take effective measures.

Following are examples of the available satellite remote sensing products for air quality measurements.

  • Aerosol Optical Depth/Thickness product provides information on aerosol in the atmosphere.
  • Fires and Thermal Anomalies product shows active fire detection (including crop burning) and thermal anomalies.
  • Normalized Difference Vegetation Index (NDVI) is a measure of greeness and health of vegetation.

 

1. Aerosol Optical Depth

2017-12-01-MODIS Combined Value-Added Aerosol Optical Depth

MODIS (Terra and Aqua) Combined Value-Added Aerosol Optical Depth (Temporal Coverage: 31 January 2013 – present). The MODIS (Terra and Aqua) Combined Value-Added Aerosol Optical Depth layer is a value-added layer based on MODIS Level 2 aerosol products. The layer can give a quick, synoptic view of the level of aerosol in the atmosphere.. MODIS Aerosol Optical Depth (or Aerosol Optical Thickness) layer indicates the level at which particles in the air (aerosols) prevent light from traveling through the atmosphere. Aerosols absorb and scatter incoming sunlight, which reduces visibility and increases the optical depth. An optical depth of less than 0.1 indicates a clear sky with maximum visibility, and a value of 1 indicates the presence of aerosols so dense that people would have difficulty seeing the Sun. Aerosols have an effect on human health, weather and the climate. Sources of aerosols include pollution from factories, smoke from fires, dust from dust storms, sea salts, and volcanic ash and smog. Aerosols compromise human health when inhaled by people with asthma or other respiratory illnesses. Aerosols also have an affect on the weather and climate by cooling or warming the earth, helping or preventing clouds from forming.
This level 3 gridded product is designed for quantitative applications including aerosol data assimilation and model validation. This layer is useful for aerosol forecasting communities such as the United States Navy Fleet Numerical Meteorology and Oceanography Center (FNMOC), National Oceanic and Atmospheric Administration (NOAA), European Centre for Medium-Range Weather Forecasts (ECMWF), National Aeronautics and Space Administration (NASA) Global Modeling Assimilation Office (GMAO), University research groups and support for field/aircraft campaigns.
The MODIS Combined Value-Added Aerosol Optical Depth layer is a near real-time layer and available as a combined Terra satellite and Aqua satellite layer (MCDAODHD). The sensor resolution is 0.5 degrees, imagery resolution is 2 km, and the temporal resolution is daily.
References: NASA Earthdata – NRT Value-Added MODIS AOD Product; GCMD Entry: MCDAODHD
2. Fire and Thermal Anomalies
nasa-worldview-fires-2017-10-15-to-2017-11-15MODIS (Terra) Fire and Thermal Anomalies Temporal Coverage: 8 May 2012 – present. The MODIS Fire and Thermal Anomalies layer shows active fire detections and thermal anomalies, such as volcanoes, and gas flares. Fires can be set naturally, such as by lightning, or by humans, whether intentionally or accidentally. Fire is often thought of as a menace and detriment to life, but in some ecosystems it is necessary to maintain the equilibrium, for example, some plants only release seeds under high temperatures that can only be achieved by fire, fires can also clear undergrowth and brush to help restore forests to good health, humans use fire in slash and burn agriculture, to clear away last year’s crop stubble and provide nutrients for the soil and to clear areas for pasture. The fire layer is useful for studying the spatial and temporal distribution of fire, to locate persistent hot spots such as volcanoes and gas flares, to locate the source of air pollution from smoke that may have adverse human health impacts.
The MODIS Fire and Thermal Anomalies product is available from the Terra (MOD14) and Aqua (MYD14) satellites as well as a combined Terra and Aqua (MCD14) satellite product. The sensor resolution is 1 km, and the temporal resolution is daily. The thermal anomalies are represented as red points (approximate center of a 1 km pixel) in the Global Imagery Browse Services (GIBS)/Worldview.
References: MOD14; MYD14; FIRMS Near Real-Time MODIS Active Fire Data; MODIS Collection 6 Active Fire Product User’s Guide
3. Normalized Difference Vegetation Index (NDVI)
nasa-worldview-2017-10-15-to-2017-11-15
Normalized Difference Vegetation Index (NDVI) (rolling 8-day) MODIS rolling 8-day Normalized Difference Vegetation Index (NDVI). The MODIS Normalized Difference Vegetation Index (NDVI) layer is a measure of the greenness and health of vegetation. The index is calculated based on how much red and near-infrared light is reflected by plant leaves. The index values range from -0.2 to 1 where higher values (0.3 to 1) indicate areas covered by green, leafy vegetation and lower values (0 to 0.3) indicate areas where there is little or no vegetation. Areas with a lot of green leaf growth, indicates the presence of chlorophyll which reflects more infrared light and less visible light, are depicted in dark green colors, areas with some green leaf growth are in light greens, and areas with little to no vegetation growth are depicted in tan colors.
The MODIS rolling 8-day NDVI layer is available as a near real-time, rolling 8-day product (MOD13Q4N) from from the Terra satellite. It is created from a rolling 8-day land surface reflectance product, MOD09Q1N. The sensor resolution is 250 m, imagery resolution is 250 m, and the temporal resolution is an 8-day product which is updated daily.
References: NASA Earth Observatory – Measuring Vegetation; NASA Earthdata – New Vegetation Indices and Surface Reflectance Products Available from LANCE; NASA NEO – Vegetation Index

Flood Monitoring from Space – ESA’s Sentinel-1

Karachi, the largest city of Pakistan received heavy monsoon rain August 30, 2017. The flood in Karachi due to heavy rains is the continuation of the similar monsoon related flooding crisis in the South East Asia region (India, Bangladesh etc.).The Flood map below is derived (subset of Karachi city ) from European Space Agency (ESA)’s Copernicus Program SENTINEL-1 Synthetic Aperture RADAR (SAR) image acquired on September 01, 2017. The green color in the map shows the flooded region.

 

 

The total rainfall derived from satellite data (GPM IMERG) for Karachi from August 29-31, 2017 is shown in Figure below:

 

 

High Resolution Optical Imager 2017 – 2030

 

Tutorials and educational resources

HYPERedu educational resources on imaging spectroscopy (Link)

Introduction to Hyperspectral Imaging – MicroImages (PDF)

Introduction to Hyperspectral Imaging (PDF)

 

Software for imaging spectroscopy

Software development (PDF) ArcGIS 10 (PDF) ISDAS (FTP)

 

ALISS3 ResourceSAT 3, 3A

ResourceSAT 3, 3A mission overview, spacecraft, data product specification, references (PDF) (Link)(Link) (PDF) (Link) (PDF)

Applications (Link) (Link) (PDF) (PDF) (PDF) (PDF)

Natural resources management, agricultural applications, forestry, etc.

 

AWIF Amozonia 1, 1A

AWIF Amozonia 1, 1A mission overview, spacecraft, data product specification, references (PDF) (Link) (Link)

Applications (Link)

Used for fire extent detection measurement, coastal and vegetation monitoring, land cover and land use mapping. WFI-2 (Amazonia-1) is the same instrument as WFI-2 (CBERS), however due differences in orbital altitude, they have different spatial resolution

 

AWIF2 Amozonia 2

AWIF Amozonia 1, 1A mission overview, spacecraft, data product specification, reference (PDF)

Application

 

GORIZONT MP Meteor MP N1, N2 

Meteor MP N1, N2 mission overview, spacecraft, data product specification, reference (Link) (Link) (PDF)

Application (Link)

HISUI ALOS-3

ALOS 3 mission overview, spacecraft, data product specification, reference (Link) (Link) (PDF) (PDF)

Application (PDF)(PDF)

 

HRMX-VNIR GISAT

GISAT mission overview, spacecraft, data product specification, reference (PDF)

Application

 

HSI Enmap 

Enmap mission overview, spacecraft, data product specification, reference (Link) (Link) (Link) (Link) (Link)

Application (PDF) (PDF) (PDF) (Link) (Link)

 

HYC PRISMA 

PRISMA mission overview, spacecraft, data product specification, reference (Link) (Link) (Link) (Link)

Application (Link) (Link) (PDF) (PDF)

 

HYS-SWIR GISAT   HYS-VNIR GISAT

HYS-SWIR GISAT mission overview, spacecraft, data product specification, reference (PDF) (Link) (Link) (Link)

Application (Link)

HYS-VNIR GISAT mission overview, spacecraft, data product specification, reference (Link)

Application (Link

 

MS SEOSAT/INGENIO 

SEOSAT/INGENIO mission overview, spacecraft, data product specification, reference (PDF) (Link) (PDF

Application (Link) (PDF)

MX CARTOSAT-3

CARTOSAT-3 mission overview, spacecraft, data product specification, reference (PDF)

Application (PDF)

 

PAN PRISMA

PAN PRISMA mission overview, spacecraft, data product specification, reference (Link) (Link) (Link)

Application (PDF)

 

PAN CARTOSAT-3

PAN CARTOSAT-3 mission overview, spacecraft, data product specification, reference (Link) (PDF)

Application

 

PAN SEOSAT/Ingenio

PAN SEOSAT/Ingenio mission overview, spacecraft, data product specification, reference (Link) (Link) (PDF)

Application (Link

 

PSC ALOS-3

Alos3_AutoD

ALOS-3 mission overview, spacecraft, data product specification, reference (Link) (Link) (Link)

Application (PDF)

 

RSI FORMAOSAT-5

FORMAOSAT-5 mission overview, spacecraft, data product specification, reference (Link) (Link) (Link)

Application (PDF) (PDF)

 

VSSC VENUS

VENUS mission overview, spacecraft, data product specification, reference (Link) (Link) (Link) (Link) (PDF) (Link)

Application (PDF) (PDF) (PDF) (PDF) (PDF)

 


 

 

Satellite remote sensing data for hydrological analyses and water resources management

Satellite remote sensing data for hydrological analyses and water resources management are listed below:

  1. Groundwater Discharges: Researcher uses satellite data to analyze the groundwater discharges. Locating ground-water discharge areas
  2. Land Water Boundaries: Satellite data has been used to convert surface features into land cover maps including water body. Water body detection and delineation with Landsat TM data
  3. Management of Water: Satellite images has important use in water management. The USA government agencies are using satellite data for monitoring decreasing water resources, especially in western part of USA by estimating past and present water use and evapotranspiration (ET). The Landsat program and water resources information needs in the United States
  4. Monitoring Flooding: Satellite image are in use to map flood damage area. Case studies
  5. Monitoring Lakes: Satellite data helps to understand and monitor changes in lake water volume (snow melt) and quality (due to spring run-off). Monitoring lake inventories and health
  6. Watersheds Mapping: Satellite data are used to map the watersheds area. Determining land use change within the dog river watershed
  7. Wetlands: Landsat data can be downloaded of few decades back, so it can be used to track the number and area of the wetlands. Mapping wetlands and riparian areas