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Paper Citation Record · LEDGER

Enhanced Drought Analysis in Bangladesh: A Machine Learning Approach for Severity Classification Using Satellite Data

As of 8 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2506.04696.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.04696 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:39:05.223835Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

15 of 15 outbound references displayed

  • verified exact4
  • verified fuzzy3
  • unresolved3
  • parse uncertain0
  • malformed identifier2
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8014a493-4a21-4e58-be10-1b313827885c · outbound

This paper cites Investigating the main reasons for the tragedy of large saline lakes: Drought, climate change, or anthropogenic activities? A call to action,.

Enhanced Drought Analysis in Bangladesh: A Machine Learning Approach for Severity Classification Using Satellite Data Investigating the main reasons for the tragedy of large saline lakes: Drought, climate change, or anthropogenic activities? A call to action,

Reference 1

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Source-reported events for the cited work

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Observation 5e233909-2403-46ad-9cb3-b28dff18ca38 · outbound

This paper cites Climate Change and Drought: the Soil Moisture Perspective,.

Enhanced Drought Analysis in Bangladesh: A Machine Learning Approach for Severity Classification Using Satellite Data Climate Change and Drought: the Soil Moisture Perspective,

Reference 2

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malformed identifier
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Source-reported events for the cited work

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Observation 93df400d-3216-48e1-8872-748bbdf80646 · outbound

This paper cites Drought forecasting using new ma- chine learning methods.

Enhanced Drought Analysis in Bangladesh: A Machine Learning Approach for Severity Classification Using Satellite Data Drought forecasting using new ma- chine learning methods

Reference 3

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malformed identifier
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Source-reported events for the cited work

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Observation ecbf25d7-a8dc-4a77-8020-3e86dcf971ee · outbound

This paper cites Lalika, A.

Enhanced Drought Analysis in Bangladesh: A Machine Learning Approach for Severity Classification Using Satellite Data Lalika, A

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a549a1ae-c5b4-49cc-bcf5-5b7568a72a1c · outbound

This paper cites Sundararajan, L.

Enhanced Drought Analysis in Bangladesh: A Machine Learning Approach for Severity Classification Using Satellite Data Sundararajan, L

Reference 5

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metadata mismatch
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 13aabd49-e9ba-48a6-a8f6-3181e2d3d08e · outbound

This paper cites Drought prediction: A comprehensive review of different drought prediction models and adopted technologies,.

Enhanced Drought Analysis in Bangladesh: A Machine Learning Approach for Severity Classification Using Satellite Data Drought prediction: A comprehensive review of different drought prediction models and adopted technologies,

Reference 6

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verified exact
doi, observed 2026-08-07T10:39:06.238588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 09fc1755-fa13-4497-bbd4-eadfde76383a · outbound

This paper cites Drought modelling by standard precipitation index (SPI) in a semi-arid climate using deep learning method: long short-term memory,.

Enhanced Drought Analysis in Bangladesh: A Machine Learning Approach for Severity Classification Using Satellite Data Drought modelling by standard precipitation index (SPI) in a semi-arid climate using deep learning method: long short-term memory,

Reference 7

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verified exact
doi, observed 2026-08-07T10:39:05.984135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 3bc542ec-a465-4c51-af13-4f68e4ee1a11 · outbound

This paper cites A review of machine learning methods for drought hazard monitoring and forecasting: Current research trends, challenges, and future research directions,.

Enhanced Drought Analysis in Bangladesh: A Machine Learning Approach for Severity Classification Using Satellite Data A review of machine learning methods for drought hazard monitoring and forecasting: Current research trends, challenges, and future research directions,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 431b4d7d-2cb4-41d9-9ccc-4f33bdd67a76 · outbound

This paper cites Enhancing crop yield prediction utilizing machine learning on Satellite- Based vegetation health indices,.

Enhanced Drought Analysis in Bangladesh: A Machine Learning Approach for Severity Classification Using Satellite Data Enhancing crop yield prediction utilizing machine learning on Satellite- Based vegetation health indices,

Reference 9

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation a3033bd9-4a3b-476d-a7cb-fc7964bbe235 · outbound

This paper cites Assessment and prediction of meteorological drought using machine learning algo- rithms and climate data,.

Enhanced Drought Analysis in Bangladesh: A Machine Learning Approach for Severity Classification Using Satellite Data Assessment and prediction of meteorological drought using machine learning algo- rithms and climate data,

Reference 10

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Source-reported events for the cited work

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Observation 0559da57-c10f-4094-a7e6-c2bed8d3776a · outbound

This paper cites Comprehensive evaluation of machine learning techniques for hydrological drought forecasting,.

Enhanced Drought Analysis in Bangladesh: A Machine Learning Approach for Severity Classification Using Satellite Data Comprehensive evaluation of machine learning techniques for hydrological drought forecasting,

Reference 11

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verified exact
doi, observed 2026-08-07T10:39:05.479315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation e79764ce-5d86-45aa-8fd1-0cab33ae8d80 · outbound

This paper cites A new method for assessment of regional drought risk: information diffusion and interval mapping adjustment based on k-means cluster points,.

Enhanced Drought Analysis in Bangladesh: A Machine Learning Approach for Severity Classification Using Satellite Data A new method for assessment of regional drought risk: information diffusion and interval mapping adjustment based on k-means cluster points,

Reference 12

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation c253170b-b6d2-45b1-8581-2dd1dc466f9c · outbound

This paper cites Optimizing spatial distribution of watershed-scale hydrologic models using Gaussian Mixture Models,.

Enhanced Drought Analysis in Bangladesh: A Machine Learning Approach for Severity Classification Using Satellite Data Optimizing spatial distribution of watershed-scale hydrologic models using Gaussian Mixture Models,

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b1117ec2-909c-43c6-84f3-2d4aa9b3a8cb · outbound

This paper cites Prediction of Worldwide Energy Resource (POWER) Project,.

Enhanced Drought Analysis in Bangladesh: A Machine Learning Approach for Severity Classification Using Satellite Data Prediction of Worldwide Energy Resource (POWER) Project,

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 5959c99a-3008-47be-837e-07c0eb63b00b · outbound

This paper cites an unresolved cited work.

Enhanced Drought Analysis in Bangladesh: A Machine Learning Approach for Severity Classification Using Satellite Data Unresolved cited work

Reference 2022

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verified exact
doi, observed 2026-08-07T10:39:05.724279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Pith citing papers

No inbound Pith citation observations are available.