CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training | Paper Citation Record

Observation c8f9e782-beff-40f1-ab56-0b91fc6a3447 · outbound

This paper cites Crucial factors of the built environment for mitigating carbon emissions.Science of The Total Environment, 806:150864, 2022.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Crucial factors of the built environment for mitigating carbon emissions.Science of The Total Environment, 806:150864, 2022

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.835705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation db0d82a8-6127-4d1d-9be7-2c5822584c2e · outbound

This paper cites Global anthropogenic emissions in urban areas: patterns, trends, and challenges.Environmental Research Letters, 16(7):074033, jul 2021.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Global anthropogenic emissions in urban areas: patterns, trends, and challenges.Environmental Research Letters, 16(7):074033, jul 2021

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.846507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a50f312b-f523-4f25-b157-883ef926aa0f · outbound

This paper cites Enabling technologies and sustainable smart cities.Sustainable Cities and Society, 61:102301, 2020.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Enabling technologies and sustainable smart cities.Sustainable Cities and Society, 61:102301, 2020

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.856154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3f81cb78-eedf-4064-8f07-caef3933c2b1 · outbound

This paper cites Using convolutional networks and satellite imagery to identify patterns in urban environments at a large scale.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Using convolutional networks and satellite imagery to identify patterns in urban environments at a large scale

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.834139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 25669967-b6e2-44ce-a01c-183faf7e2f79 · outbound

This paper cites Satellite data for the air pollution mapping.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Satellite data for the air pollution mapping

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.855150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a7ab2648-7c30-4ad9-bd21-0d21ea4e1bea · outbound

This paper cites A review of satellite-based global agricultural monitoring systems available for africa.Global Food Security, 29:100543, 2021.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training A review of satellite-based global agricultural monitoring systems available for africa.Global Food Security, 29:100543, 2021

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.853170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a0870606-6338-4f0c-b748-011b0879772b · outbound

This paper cites Reforestree: A dataset for estimating tropical forest carbon stock with deep learning and aerial imagery.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Reforestree: A dataset for estimating tropical forest carbon stock with deep learning and aerial imagery

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.860728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5695a8c5-9e6a-44f0-9aaf-c8f7d04a769f · outbound

This paper cites Planet application program interface: In space for life on earth.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Planet application program interface: In space for life on earth

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.865258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4753ea84-2934-4464-96c7-13fbb02c780b · outbound

This paper cites Position: mission critical–satellite data is a distinct modality in machine learning.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Position: mission critical–satellite data is a distinct modality in machine learning

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.843885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5c3ee907-e511-459c-82b8-8c75fdec701e · outbound

This paper cites Streetvizor: Visual exploration of human-scale urban forms based on street views.IEEE Transactions on Visualization and Computer Graphics, 24(1):1004–1013, 2017.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Streetvizor: Visual exploration of human-scale urban forms based on street views.IEEE Transactions on Visualization and Computer Graphics, 24(1):1004–1013, 2017

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.783479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c60553a3-0615-493c-9742-fd561b952e04 · outbound

This paper cites Mapping sky, tree, and building view factors of street canyons in a high-density urban environment.Building and Environment, 134:155–167, 2018.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Mapping sky, tree, and building view factors of street canyons in a high-density urban environment.Building and Environment, 134:155–167, 2018

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.781391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6101dcd4-0463-46d1-bdcc-f0bc29d748eb · outbound

This paper cites Urban visual intelligence: Uncovering hidden city profiles with street view images.Proceedings of the National Academy of Sciences, 120(27):e2220417120, 2023.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Urban visual intelligence: Uncovering hidden city profiles with street view images.Proceedings of the National Academy of Sciences, 120(27):e2220417120, 2023

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.839935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b8e8263d-3feb-4d64-98e9-304634f5435e · outbound

This paper cites Street view imagery in urban analytics and gis: A review.Landscape and Urban Planning, 215:104217, 2021.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Street view imagery in urban analytics and gis: A review.Landscape and Urban Planning, 215:104217, 2021

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.841872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9857f61e-3bf6-405f-bff5-00f2b4c494be · outbound

This paper cites Investigating the associ- ation between streetscapes and human walking activities using google street view and human trajectory data.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Investigating the associ- ation between streetscapes and human walking activities using google street view and human trajectory data

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.858001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f5f3bdf5-f07d-4e45-a5eb-d9afc7a38069 · outbound

This paper cites 3d building reconstruction from single street view images using deep learning.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training 3d building reconstruction from single street view images using deep learning

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.779023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9bb9259c-a54c-47e2-9c0f-97037b16a778 · outbound

This paper cites Using google street view to reveal environmental justice: Assessing public perceived walkability in macroscale city.Landscape and Urban Planning, 244:104995, 2024.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Using google street view to reveal environmental justice: Assessing public perceived walkability in macroscale city.Landscape and Urban Planning, 244:104995, 2024

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.867183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0f559e99-aadf-4d33-b7ea-007ed22ae988 · outbound

This paper cites Evaluating the multi-seasonal impacts of urban blue-green space combination models on cooling and carbon-saving capacities.Building and Environment, 266:112045, 2024.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Evaluating the multi-seasonal impacts of urban blue-green space combination models on cooling and carbon-saving capacities.Building and Environment, 266:112045, 2024

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.863084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation faf8b469-8647-4bc0-bd3d-068811a76ed4 · outbound

This paper cites Estimating carbon dioxide emissions from power plant water vapor plumes using satellite imagery and machine learning.Remote Sensing, 16(7):1290, 2024.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Estimating carbon dioxide emissions from power plant water vapor plumes using satellite imagery and machine learning.Remote Sensing, 16(7):1290, 2024

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.836163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e198fc23-69c8-46af-86f7-4c9160e0162d · outbound

This paper cites Estimating carbon dioxide emissions in two california cities using bayesian inversion and satellite measurements.Geophysical Research Letters, 51(20):e2024GL111150, 2024.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Estimating carbon dioxide emissions in two california cities using bayesian inversion and satellite measurements.Geophysical Research Letters, 51(20):e2024GL111150, 2024

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.821219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3cb09364-f7b8-4f00-9cf6-04d5ff898233 · outbound

This paper cites Estimating carbon emissions in urban functional zones using multi-source data: A case study in beijing.Building and Environment, 212:108804, 2022.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Estimating carbon emissions in urban functional zones using multi-source data: A case study in beijing.Building and Environment, 212:108804, 2022

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.823264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 15fbc4f4-6af5-4dab-ba31-10327dfb82b3 · outbound

This paper cites Uncovering the spatiotemporal impacts of built environment on traffic carbon emissions using multi-source big data.Land Use Policy, 129:106621, 2023.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Uncovering the spatiotemporal impacts of built environment on traffic carbon emissions using multi-source big data.Land Use Policy, 129:106621, 2023

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.850200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c56f2645-7a1a-4a8f-9b8c-9e482302187c · outbound

This paper cites Carbon emission estimation at the urban functional zone scale: Integrating multi-source data and machine learning approach.Energy and Buildings, page 115832, 2025.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Carbon emission estimation at the urban functional zone scale: Integrating multi-source data and machine learning approach.Energy and Buildings, page 115832, 2025

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.817066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4e4d6c1e-5c6a-4f06-807d-055eaa9e5f7d · outbound

This paper cites Urbanmllm: Joint learning of cross-view imagery for urban understanding.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Urbanmllm: Joint learning of cross-view imagery for urban understanding

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.823616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 29bd8a04-391a-47d1-b2f4-876fce88b399 · outbound

This paper cites Urbanvlp: Multi-granularity vision-language pretraining for urban socioeconomic indicator prediction.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Urbanvlp: Multi-granularity vision-language pretraining for urban socioeconomic indicator prediction

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.891255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7e0d9e17-08dd-40f4-9374-f813a507504c · outbound

This paper cites an unresolved cited work.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-07-09T15:06:18.802473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 55d250c3-d810-4751-85ea-69f932490710 · outbound

This paper cites A neural network model for forecasting co2 emission.AGRIS on-line Papers in Economics and Informatics, 6(2):31–36, 2014.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training A neural network model for forecasting co2 emission.AGRIS on-line Papers in Economics and Informatics, 6(2):31–36, 2014

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.830113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 95619359-2308-4e9c-a3d8-26f2bcb666ab · outbound

This paper cites an unresolved cited work.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-07-09T15:06:18.843442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 512b7910-9eac-4451-9e31-d18fcef863db · outbound

This paper cites an unresolved cited work.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-07-09T15:06:18.871275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7d1e8ecf-08cd-437e-8655-40a6c7e750c7 · outbound

This paper cites an unresolved cited work.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-07-09T15:06:18.774331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 347e8bd5-3efd-4b38-94de-885c1e9dd8ab · outbound

This paper cites Exploring spatio- temporal carbon emission across passenger car trajectory data.IEEE Transactions on Intelligent Transportation Systems, 2024.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Exploring spatio- temporal carbon emission across passenger car trajectory data.IEEE Transactions on Intelligent Transportation Systems, 2024

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.355441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 28dcade0-1a6d-4ff8-ae40-19de8db400ba · outbound

This paper cites Real time estimation of carbon emissions for industrial users based on load monitoring in advanced metering infrastructure.Journal of Cleaner Production, 483:144226, 2024.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Real time estimation of carbon emissions for industrial users based on load monitoring in advanced metering infrastructure.Journal of Cleaner Production, 483:144226, 2024

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.837702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 81c4793b-50ea-4935-b872-f1cb93501435 · outbound

This paper cites The estimation of building carbon emission using nighttime light images: A comparative study at various spatial scales.Sustainable Cities and Society, 101:105066, 2024.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training The estimation of building carbon emission using nighttime light images: A comparative study at various spatial scales.Sustainable Cities and Society, 101:105066, 2024

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.831609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5097cf73-7b63-4436-8608-5562647e7d0c · outbound

This paper cites What drives urban carbon emission efficiency?–spatial analysis based on nighttime light data.Applied Energy, 312:118772, 2022.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training What drives urban carbon emission efficiency?–spatial analysis based on nighttime light data.Applied Energy, 312:118772, 2022

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.814093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 06d93499-6eaa-4f38-95f3-28474fc51d4d · outbound

This paper cites Correcting the saturation effect in dmsp/ols stable nighttime light products based on radiance-calibrated data.IEEE Transactions on Geoscience and Remote Sensing, 60:1–11, 2021.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Correcting the saturation effect in dmsp/ols stable nighttime light products based on radiance-calibrated data.IEEE Transactions on Geoscience and Remote Sensing, 60:1–11, 2021

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.815972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ae9c486c-d714-473c-96d8-50ee3e5fdff1 · outbound

This paper cites an unresolved cited work.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Unresolved cited work

Reference 35

Resolution: unresolved; raw_fallback, observed 2026-07-09T15:06:18.858757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d7ef69fc-3d1b-4340-90a3-dfbfa79ed8d9 · outbound

This paper cites Phenological classification using deep learning and the sentinel-2 satellite to identify priority afforestation sites in north korea.Remote Sensing, 13(15):2946, 2021.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Phenological classification using deep learning and the sentinel-2 satellite to identify priority afforestation sites in north korea.Remote Sensing, 13(15):2946, 2021

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.821526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ea5d9b42-c15e-4af4-b413-fb3c55c038e1 · outbound

This paper cites Inferring carbon dioxide emissions from power plants using satellite imagery and machine learning.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Inferring carbon dioxide emissions from power plants using satellite imagery and machine learning

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.833527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e5e0d325-6282-4ae9-810d-ebd899616e65 · outbound

This paper cites Ai-powered computer vision for remote sensing and carbon emission detection in industrial and urban environments.Iconic Research and Engineering Journals, 7(10):490–505, 2024.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Ai-powered computer vision for remote sensing and carbon emission detection in industrial and urban environments.Iconic Research and Engineering Journals, 7(10):490–505, 2024

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.869271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation db6fcdf8-b51e-4725-8451-7f9da851f479 · outbound

This paper cites an unresolved cited work.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Unresolved cited work

Reference 39

Resolution: unresolved; raw_fallback, observed 2026-07-09T15:06:18.799342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5c76becc-053e-42cb-8038-f87c5ae28b3b · outbound

This paper cites Impact of building materials for the facade on energy consumption and carbon emissions (case study of residential buildings in tehran).Energy Engineering, 122(9), 2025.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Impact of building materials for the facade on energy consumption and carbon emissions (case study of residential buildings in tehran).Energy Engineering, 122(9), 2025

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.797629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9b1c40a0-e217-46b7-bdeb-c23b5e025856 · outbound

This paper cites Urban region representation learning with openstreetmap building footprints.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Urban region representation learning with openstreetmap building footprints

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.794268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 87b96f4c-4e25-4aa4-bbaf-a2c94ca7e224 · outbound

This paper cites Flexireg: Flexible urban region representation learning.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Flexireg: Flexible urban region representation learning

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.813152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5e8043c5-958b-4909-8384-6d881cdfc993 · outbound

This paper cites Geoclip: Clip-inspired alignment between locations and images for effective worldwide geo-localization.Advances in Neural Information Processing Systems, 36:8690–8701, 2023.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Geoclip: Clip-inspired alignment between locations and images for effective worldwide geo-localization.Advances in Neural Information Processing Systems, 36:8690–8701, 2023

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.769633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f3c17fb8-cbaf-47ed-a317-4c0a3110158a · outbound

This paper cites Satclip: Global, general-purpose location embeddings with satellite imagery.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Satclip: Global, general-purpose location embeddings with satellite imagery

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.776739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7e15e482-a996-4942-906c-d8034806516a · outbound

This paper cites Img2loc: Revisiting image geolocalization using multi-modality foundation models and image-based retrieval- augmented generation.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Img2loc: Revisiting image geolocalization using multi-modality foundation models and image-based retrieval- augmented generation

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.804509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c8bc374c-9c05-4a95-a341-e68f9e491f0f · outbound

This paper cites Towards Interpretable Geo-localization: a Concept-Aware Global Image-GPS Alignment Framework.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Towards Interpretable Geo-localization: a Concept-Aware Global Image-GPS Alignment Framework

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-07-09T15:06:17.956004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fd39edea-f28c-4f1b-94cd-d2edc052ea90 · outbound

This paper cites Remoteclip: A vision language foundation model for remote sensing.IEEE Transactions on Geoscience and Remote Sensing, 62:1–16.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Remoteclip: A vision language foundation model for remote sensing.IEEE Transactions on Geoscience and Remote Sensing, 62:1–16

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.808993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 76d3d2b9-d099-47a8-a2a1-beb1d625fac5 · outbound

This paper cites Urbanclip: Learning text-enhanced urban region profiling with contrastive language-image pretraining from the web.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Urbanclip: Learning text-enhanced urban region profiling with contrastive language-image pretraining from the web

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.854395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b91d18f9-4678-46d5-9805-9c878d8235d5 · outbound

This paper cites an unresolved cited work.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Unresolved cited work

Reference 49

Resolution: unresolved; raw_fallback, observed 2026-07-09T15:06:18.837985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7d6dbbf0-4534-4635-8575-bf2d97604230 · outbound

This paper cites Geochat: Grounded large vision-language model for remote sensing.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Geochat: Grounded large vision-language model for remote sensing

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.883574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 638515ec-9e3c-4101-8783-bd82ad049dc8 · outbound

This paper cites Earthgpt: A universal multimodal large language model for multisensor image comprehension in remote sensing domain.IEEE Transactions on Geoscience and Remote Sensing, 62:1–20.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Earthgpt: A universal multimodal large language model for multisensor image comprehension in remote sensing domain.IEEE Transactions on Geoscience and Remote Sensing, 62:1–20

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.885574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ba94850f-7733-4127-a104-f1207ae71d1b · outbound

This paper cites Earthgpt-x: A spatial mllm for multilevel multisource remote sensing imagery understanding with visual prompting.IEEE Transactions on Geoscience and Remote Sensing, 63:1–21, 2025.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Earthgpt-x: A spatial mllm for multilevel multisource remote sensing imagery understanding with visual prompting.IEEE Transactions on Geoscience and Remote Sensing, 63:1–21, 2025

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.889405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 74bcbcc9-9dee-4d4f-a526-8484be4055ca · outbound

This paper cites AddressVLM: Cross-view Alignment Tuning for Image Address Localization using Large Vision-Language Models.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training AddressVLM: Cross-view Alignment Tuning for Image Address Localization using Large Vision-Language Models

Reference 53

Resolution: verified exact; local_arxiv, observed 2026-07-09T15:06:17.958785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6ad1f943-7535-4896-94d3-fbb61a11f375 · outbound

This paper cites Qwen2.5-VL Technical Report.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Qwen2.5-VL Technical Report

Reference 54

Resolution: verified exact; local_arxiv, observed 2026-07-09T15:06:17.960717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5b5a8057-bdf8-41ae-8e70-ce5724c304f5 · outbound

This paper cites Learning transferable visual models from natural language supervision.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Learning transferable visual models from natural language supervision

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.881749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6c18e1a9-9805-4320-81d1-6dc9cb57c921 · outbound

This paper cites Attention is all you need.Advances in Neural Information Processing Systems, 30.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Attention is all you need.Advances in Neural Information Processing Systems, 30

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.875871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c227f6a2-e2ab-403c-8935-09763f63da0e · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 57

Resolution: verified exact; local_arxiv, observed 2026-07-09T15:06:17.957704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1e9fa5ba-4f81-4263-8172-10a34c3132a0 · outbound

This paper cites Google Maps Platform.https://maps.google.com, 2025.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Google Maps Platform.https://maps.google.com, 2025

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.856996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7aa70ec2-f0a0-409b-81bd-e8dbb442cdf6 · outbound

This paper cites Baidu Maps API.https://lbsyun.baidu.com, 2025.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Baidu Maps API.https://lbsyun.baidu.com, 2025

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.825594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e694f521-0ed0-4187-be35-625304e4c5df · outbound

This paper cites The open-source data inventory for anthropogenic co2 (odiac) 2023, 2023.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training The open-source data inventory for anthropogenic co2 (odiac) 2023, 2023

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.873707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d61c3240-ef6b-4a93-820c-f1855983f13e · outbound

This paper cites Effects of 3d urban morphology on co2 emissions using machine learning: Towards spatially tailored low-carbon strategies in central wuhan, china.Urban Climate, 57:102122, 2024.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Effects of 3d urban morphology on co2 emissions using machine learning: Towards spatially tailored low-carbon strategies in central wuhan, china.Urban Climate, 57:102122, 2024

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.877861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7176b2d7-ffcf-4cb3-b50b-12cd01119a8e · outbound

This paper cites Impact of compact city on carbon emission reduction based on urban size: A spatial analysis using satellite imagery.Sustainable Cities and Society, 126:106326, 2025.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Impact of compact city on carbon emission reduction based on urban size: A spatial analysis using satellite imagery.Sustainable Cities and Society, 126:106326, 2025

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.879811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3c36ffc8-50c7-4d69-8ced-9ccba16dd9b5 · outbound

This paper cites Deep residual learning for image recognition.

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training Deep residual learning for image recognition

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T15:06:18.887466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers