Articles published in Journal of Remote Sensing & GIS have been cited by esteemed scholars and scientists all around the world. Journal of Remote Sensing & GIS has got h-index 20, which means every article in Journal of Remote Sensing & GIS has got 20 average citations.

Following are the list of articles that have cited the articles published in Journal of Remote Sensing & GIS.

  2022 2021 2020 2019 2018

Year wise published articles

61 76 48 13 31

Year wise citations received

304 294 211 148 74
Journal total citations count 1229
Journal Impact Factor 1.58
Journal 5 years Impact Factor 2.63
Journal CiteScore 4.47
Journal h-index 20
Important citations

Mapping forest dynamics in Bangladesh from satellite images: Implications for the global REDD+ program

Identifying local-scale meteorological conditions favorable to large fires in Brazil

CLASlite unmixing of Landsat images to estimate REDD+ activity data for deforestation in a Bangladesh forest

COMBINATION OF SPECTRAL INDICES FOR BURNED AREA DETECTION IN THE BRAZILIAN AMAZONIA

Burning in southwestern Brazilian Amazonia, 2016–2019

REDD+ project design study for quantifying activity data for historic forest degradation in a Bangladesh forest using Landsat data

Improving the spatial-temporal analysis of Amazonian fires

Intercomparison of Burned Area Products and Its Implication for Carbon Emission Estimations in the Amazon

Translating Fire Impacts in Southwestern Amazonia into Economic Costs

Dynamics of forest fires in the southwestern Amazon

Methodological contributions for obtaining altimetric information required in the local assessment of flood threats from new geospatial technologies

A COLLABORATIVE APPROACH FOR DISASTER RISK REDUCTION: MAPPING SOCIAL LEARNING WITH MISTAWASIS NÊHIYAWAK

Satellite image fusion and PSO optimization algorithm to improve the evaluation of water bodies, focusing on flood monitoring

Cross-Border Urban Change Detection and Growth Assessment for Mexican-USA Twin Cities

Measurement to Management: Study of Remote Sensing Techniques for Flood Disaster Management

Comparative analysis of ground elevations derived from RPAS-based LiDAR and ground-based TLS/RTK data

Integrating water-classified returns in DTM generation to increase accuracy of stream delineations and geomorphic analyses

G.I.S. IMPLEMENTATION ON DAM-BREAK FLOOD VULNERABILITY ANALYSIS – A CASE STUDY OF C?T?M?R??TI DAM, BOTO?ANI, ROMANIA

Shoreline Solutions: Guiding Efficient Data Selection for Coastal Risk Modeling and the Design of Adaptation Interventions

Deep Learning Methods for 3D Aerial and Satellite Data