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Identification of Soil Types and Salinity Using MODIS Terra Data and Machine Learning Techniques in...

Identification of Soil Types and Salinity Using MODIS Terra Data and Machine Learning Techniques in...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_0fd6d9ee49c44660842da960d7c831d3

Identification of Soil Types and Salinity Using MODIS Terra Data and Machine Learning Techniques in Multiple Regions of Pakistan

About this item

Full title

Identification of Soil Types and Salinity Using MODIS Terra Data and Machine Learning Techniques in Multiple Regions of Pakistan

Publisher

Basel: MDPI AG

Journal title

Sensors (Basel, Switzerland), 2023-09, Vol.23 (19), p.8121

Language

English

Formats

Publication information

Publisher

Basel: MDPI AG

More information

Scope and Contents

Contents

Soil, a significant natural resource, plays a crucial role in supporting various ecosystems and serves as the foundation of Pakistan’s economy due to its primary use in agriculture. Hence, timely monitoring of soil type and salinity is essential. However, traditional methods for identifying soil types and detecting salinity are time-consuming, requ...

Alternative Titles

Full title

Identification of Soil Types and Salinity Using MODIS Terra Data and Machine Learning Techniques in Multiple Regions of Pakistan

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_0fd6d9ee49c44660842da960d7c831d3

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_0fd6d9ee49c44660842da960d7c831d3

Other Identifiers

ISSN

1424-8220

E-ISSN

1424-8220

DOI

10.3390/s23198121

How to access this item