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)

 


 

 

Advertisements

Monitoring Billion Tree Planation with Remote Sensing Satellite data

Khyber Pakhtunkhaw (KPK) provincial government in Pakistan, govern by the Pakistan Tehreek-e-Insaf (PTI) party launched a reforestation program named “Billion tree Tsunami”, in 2015 (@btap2015). Imran Khan (@ImranKhanPTI), a cricket super star turned politician is the head of PTI party, Prime Minister of Pakistan and main driver behind this massive plantation campaign to turn degraded into forested land.  The important aspect of this project is to monitor and identify the growth of these plantation regions. The remote sensing and Geographic Information Systems (GIS) tools provides this near-real-time (NRT) information at low cost compared to field campaigns.

The well known method to identify and monitor land surface changes using satellite remote sensing data utilizes a combination of band thresholding and optical indices (such as Normalized Difference Vegetation Index – NDVI) to separate land surface features. Applying this approach to two separate images by a given period of time allows changes in the extent of the area of interest to be identified.  The atmospheric correction to the two images  separated over time, extent of land can be compared. allowing for changes to be identified. this approach will provide an excellent alternative to field level change detection methods in challenging environments across Pakistan. We tested this approach for Bannu forest region (as shown in the Figure 2).  The Figure 1 shows the land cover map of Bannu region for the year 2015.

  Figure 1: Land Cover map of Bannu forest region (credit to ESA CCI)

  Figure 2: Map of Bannu forest region (credit to Billion Tree Tsunami website)

Two Landsat 8 images are used for this study area acquired in June 01, 2013 and June 12, 2017. The Landsat 8 images are freely available from the United States Geological Survey (USGS) “EarthExplorer” (https://earthexplorer.usgs.gov/). The images were converted into surface reflectance before NDVI calculations using a standardised approach ( for detail check  http://landsat.usgs.gov/CDR_LSR.php).

 

Figure 3: NDVI map of Bannu forest region derived from Landsat 8 image acquired on June 01, 2013.

Figure 4: NDVI map of Bannu forest region derived from Landsat 8 image acquired on June 12, 2017.

Figure 5: NDVI map in KMZ format of Bannu forest region derived from Landsat 8 image acquired on June 01, 2013 shown in google earth.

Figure 6: NDVI map in KMZ format of Bannu forest region derived from Landsat 8 image acquired on June 12, 2017 shown in google earth.


Please contact me for more detail.  email: kshahidk@gmail.com  twitter: @kshahidkOttawa