LISS-IV
E912244
LISS-IV is a high-resolution multispectral imaging sensor used on Indian remote sensing satellites for detailed land and resource observation.
All labels observed (1)
| Label | Occurrences |
|---|---|
| LISS-IV canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T11146314 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LISS-IV Context triple: [IRS-P6, payload, LISS-IV]
-
A.
LISS-III
LISS-III is a multispectral imaging sensor used on Indian Remote Sensing satellites to capture medium-resolution Earth observation data for applications such as land use, agriculture, and forestry.
-
B.
LISS-I
LISS-I is a multispectral imaging sensor used on early Indian Remote Sensing (IRS) satellites to capture medium-resolution Earth observation data for applications like agriculture and land-use mapping.
-
C.
LISS-II
LISS-II is a multispectral imaging sensor used on early Indian Remote Sensing (IRS) satellites to capture medium-resolution Earth observation data for applications like agriculture and land-use mapping.
-
D.
LISS-I sensor
The LISS-I sensor is a multispectral imaging instrument used on early Indian Remote Sensing (IRS) satellites to capture medium-resolution Earth observation data for applications like agriculture, forestry, and land-use mapping.
-
E.
LISS-II sensor
The LISS-II sensor is a multispectral imaging instrument used on early Indian Remote Sensing (IRS) satellites to capture medium-resolution Earth observation data for applications like agriculture, forestry, and land-use mapping.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: LISS-IV Target entity description: LISS-IV is a high-resolution multispectral imaging sensor used on Indian remote sensing satellites for detailed land and resource observation.
-
A.
LISS-III
LISS-III is a multispectral imaging sensor used on Indian Remote Sensing satellites to capture medium-resolution Earth observation data for applications such as land use, agriculture, and forestry.
-
B.
LISS-I
LISS-I is a multispectral imaging sensor used on early Indian Remote Sensing (IRS) satellites to capture medium-resolution Earth observation data for applications like agriculture and land-use mapping.
-
C.
LISS-II
LISS-II is a multispectral imaging sensor used on early Indian Remote Sensing (IRS) satellites to capture medium-resolution Earth observation data for applications like agriculture and land-use mapping.
-
D.
LISS-I sensor
The LISS-I sensor is a multispectral imaging instrument used on early Indian Remote Sensing (IRS) satellites to capture medium-resolution Earth observation data for applications like agriculture, forestry, and land-use mapping.
-
E.
LISS-II sensor
The LISS-II sensor is a multispectral imaging instrument used on early Indian Remote Sensing (IRS) satellites to capture medium-resolution Earth observation data for applications like agriculture, forestry, and land-use mapping.
- F. None of above. chosen
Statements (48)
| Predicate | Object |
|---|---|
| instanceOf |
multispectral imaging sensor
ⓘ
remote sensing instrument ⓘ |
| abbreviationFor | Linear Imaging Self-Scanning Sensor-IV NERFINISHED ⓘ |
| applicationDomain |
earth observation
ⓘ
remote sensing ⓘ |
| countryOfOrigin | India ⓘ |
| dataProduct |
ortho-rectified images
ⓘ
thematic maps ⓘ |
| dataType | high-resolution imagery ⓘ |
| dataUser |
commercial mapping organizations
ⓘ
government agencies ⓘ research institutions ⓘ |
| designedFor | detailed land and resource observation ⓘ |
| generation | fourth generation of LISS sensors ⓘ |
| hostMissionType | Resourcesat series NERFINISHED ⓘ |
| operator | Indian Space Research Organisation ⓘ |
| platformOrbitType | sun-synchronous polar orbit ⓘ |
| primaryUse |
agricultural monitoring
ⓘ
disaster assessment ⓘ forest mapping ⓘ land observation ⓘ land use and land cover mapping ⓘ resource monitoring ⓘ urban mapping ⓘ |
| relatedInstrument |
LISS-I
NERFINISHED
ⓘ
LISS-II NERFINISHED ⓘ LISS-III NERFINISHED ⓘ |
| spatialDetail | high spatial resolution ⓘ |
| spatialResolution | 5.8 m ⓘ |
| spectralBand |
green band
ⓘ
near infrared band ⓘ red band ⓘ |
| spectralRange |
near infrared
ⓘ
visible ⓘ |
| spectralType | multispectral ⓘ |
| swathMode |
mono
ⓘ
stereo ⓘ |
| swathWidth |
about 23 km in mono mode
ⓘ
about 70 km in multi-spectral mode (with tilting) ⓘ |
| temporalCoverage | repetitive coverage of the same area ⓘ |
| tiltCapability | up to about ±26 degrees across track ⓘ |
| usedIn |
crop acreage estimation
ⓘ
environmental monitoring ⓘ water resources assessment ⓘ |
| usedOn |
IRS-P6 Resourcesat-1
NERFINISHED
ⓘ
Indian Remote Sensing satellites NERFINISHED ⓘ Resourcesat-2 NERFINISHED ⓘ Resourcesat-2A NERFINISHED ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: LISS-IV Description of subject: LISS-IV is a high-resolution multispectral imaging sensor used on Indian remote sensing satellites for detailed land and resource observation.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.