Evidence map›Paper›PMID 38421498›Full record

ArticleEnvironmental monitoring and assessment2024

Assessing tea plantations biophysical and biochemical characteristics in Northeast India using satellite data.

Trinath Mahato, Bikash Ranjan Parida, Somnath Bar

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Article in Environmental monitoring and assessment, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Trinath MahatoDepartment of Geoinformatics, School of Natural Resource Management, Central University of Jharkhand, Ranchi, 835222, India.
Bikash Ranjan ParidaDepartment of Geoinformatics, School of Natural Resource Management, Central University of Jharkhand, Ranchi, 835222, India. bikash.parida@cuj.ac.in.ORCID http://orcid.org/0000-0001-7444-573X
Somnath BarDepartment of Geography and Environmental Science, University of Southampton, Highfield, Southampton, SO17 1BJ, UK.

Funding

University Grants Commission F.4-5(209-FRP)/2015/BSR
6 · The paper itself

Abstract

Despite advancements in using multi-temporal satellite data to assess long-term changes in Northeast India's tea plantations, a research gap exists in understanding the intricate interplay between biophysical and biochemical characteristics. Further exploration is crucial for precise, sustainable monitoring and management. In this study, satellite-derived vegetation indices and near-proximal sensor data were deployed to deduce various physico-chemical characteristics and to evaluate the health conditions of tea plantations in northeast India. The districts, such as Sonitpur, Jorhat, Sibsagar, Dibrugarh, and Tinsukia in Assam were selected, which are the major contributors to the tea industry in India. The Sentinel-2A (2022) data was processed in the Google Earth Engine (GEE) cloud platform and utilized for analyzing tea plantations biochemical and biophysical properties. Leaf chlorophyll (C

Indexed as

Camellia sinensisEnvironmental MonitoringIndiaNitrogenTeaNitrogenTeaChlorophyll contentGoogle Earth EngineLAINitrogen contentRemote sensingTea plantations

Identifiers

PMID38421498

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.