LISS-III
E906764
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.
All labels observed (1)
| Label | Occurrences |
|---|---|
| LISS-III canonical | 5 |
How this entity was disambiguated
This entity first appeared as the object of triple T11146176 — 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-III Context triple: [IRS-1C, payload, LISS-III]
-
A.
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.
-
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-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.
-
D.
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.
-
E.
LSS
LSS is the station code for LaSalle Street Station, a major commuter rail terminal in downtown Chicago, Illinois.
- 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-III Target entity description: 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.
-
A.
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.
-
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-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.
-
D.
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.
-
E.
LSS
LSS is the station code for LaSalle Street Station, a major commuter rail terminal in downtown Chicago, Illinois.
- F. None of above. chosen
Statements (47)
| Predicate | Object |
|---|---|
| instanceOf |
Earth observation instrument
ⓘ
multispectral imaging sensor ⓘ |
| application |
agriculture monitoring
ⓘ
crop acreage estimation ⓘ disaster management support ⓘ drought assessment ⓘ forestry monitoring ⓘ land cover classification ⓘ land use mapping ⓘ watershed management ⓘ |
| countryOfOrigin | India ⓘ |
| dataAvailability | commercially distributed ⓘ |
| dataFormat | digital raster data ⓘ |
| dataProvider |
NRSC
NERFINISHED
ⓘ
National Remote Sensing Centre NERFINISHED ⓘ |
| dataType | medium-resolution imagery ⓘ |
| dataUser |
Indian government agencies
NERFINISHED
ⓘ
international remote sensing community ⓘ |
| designedBy | Indian Space Research Organisation NERFINISHED ⓘ |
| imagingMode | pushbroom scanner ⓘ |
| operator |
Indian Space Research Organisation
ⓘ
surface form:
ISRO
Indian Space Research Organisation ⓘ |
| platformType | sun-synchronous orbit satellites ⓘ |
| purpose |
environmental monitoring
ⓘ
natural resources management ⓘ operational Earth observation ⓘ |
| relatedTo |
LISS-I
ⓘ
LISS-II NERFINISHED ⓘ LISS-IV NERFINISHED ⓘ |
| spatialResolution | 23.5 m ⓘ |
| spectralBand |
green band
ⓘ
near infrared band ⓘ red band ⓘ shortwave infrared band ⓘ |
| spectralRange |
near infrared
ⓘ
shortwave infrared ⓘ visible ⓘ |
| spectralType | multispectral ⓘ |
| swathWidth | 141 km ⓘ |
| usedFor |
change detection studies
ⓘ
time-series analysis of vegetation ⓘ |
| usedOn |
IRS-1C
NERFINISHED
ⓘ
IRS-1D NERFINISHED ⓘ Indian Remote Sensing satellites NERFINISHED ⓘ Resourcesat-1 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-III Description of subject: 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.
Referenced by (5)
Full triples — surface form annotated when it differs from this entity's canonical label.