Work

Investigation of the Use of Some Satellite Indices in Monitoring Leaf Area Index in Cotton Plants

Year: 2025

Type: article

Abstract: Leaf Area Index (LAI) is accepted as one of the basic indicators of plant development. Direct LAI estimation methods require intensive labor and time. This work; In order to realize the LAI estimation without damage, in a shorter time and with less labor-intensive effort, it was made on a total of 27 parcels where cotton cultivation is carried out in 8 villages in Artuklu and Kızıltepe districts of Mardin province. In the study, the relationships between terrestrial LAI observation and ARVI, GARI, EVI2, NDVI, WDRVI, MSI, NBR, NDMI, MTVI2, SIPI, OSAVI, SAVI indices derived from Sentinel-2 satellite data were examined. All indices were found significant at the 0.01 level. ARVI and GARI having atmospheric correction effect (R2 =0.77-0.76, respectively), basic indices EVI2, NDVI and WDRVI (R2 =0.74-0.74-0.75, respectively), MSI, NBR and NDMI with plant moisture content sensitivity (R2=0.77-0.79-0.77, respectively) showed high relationships. In addition, pigment sensitivity MTVI2 and SIPI (R2 =0.73-0.74), OSAVI and SAVI designed against background soil effect (R2 =0.74-0.74) showed high relation. It is recommended that these indices be used as a good LAI estimator in cotton plant.

Source: Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi

DOI: 10.21597/jist.1549664

Authors: Serkan Kılıçaslan, Remzi Ekinci, Mehmet Cengiz Arslanoğlu

Institutions: Ministry of Agriculture and Forestry, Dicle University, Batman University

Language: English

Topic: Remote Sensing in Agriculture

Subfield: Ecology

Field: Environmental Science

Domain: Physical Sciences

SDG: Zero hunger

Open Access status: hybrid

Funder: Dicle Üniversitesi