Integrating Geo-AI with GIS and RSfor Analyzing Land Cover Transformationand Its Impacts in Henan

Understanding the interaction between land use and land surface temperature (LST) is essential for tackling the increasing problems of urbanization, environmental degradation, and climate change.This research explores the spatial and temporal patterns of Land Use and Land Cover (LULC) and their effect on LST in Henan Province, China, between 1990 and 2024, spanning 34 years.Using multi-temporal Landsat imagery, supervised classification using the Random Forest algorithm, and cloud-based processing in Google Earth Engine (GEE), we have mapped LULC changes and extracted LST values with high spatial resolution and temporal consistency.The findings indicate extensive land transformation, with urban areas increasing by more than 181%, mainly at the cost of cropland, which decreased by almost 11%.Concurrently, LST rose markedly, with maximum surface temperatures increasing from 43.2C to 51.3C.Built-up and barren land exhibited the highest mean LST values, while forests and water bodies consistently recorded cooler temperatures, highlighting the role of vegetative cover and hydrological features in mitigating surface heat.To quantify these relationships, Pearson correlation analysis was performed between the area of each LULC class and its corresponding LST.The results showed significant positive correlations between land built-up and LST (r>0.94), and significant negative correlations for cropland and forest cover (r<-0.95),affirming the urbanization-and land-degradation-related thermal amplification.The research establishes the pivotal relationship between LULC changes and surface thermal trends, providing an actionable geospatial model for environmental monitoring and land management.The incorporation of long-term satellite data with statistical correlation produces actionable information for policymakers, urban planners, and sustainability stakeholders.With Henan and much of the rest of the world continuing to urbanize rapidly, this study reinforces the need to balance development with ecological resilience to reduce increasing surface temperatures and their larger climate impacts.

Authors

Institutions

Publication Details

Journal
Polish Journal of Environmental Studies
Published
2025-09-25
DOI
https://doi.org/10.15244/pjoes/209834
Primary Topic
Remote Sensing and Land Use
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integrating Geo-AI with GIS and RSfor Analyzing Land Cover Transformationand Its Impacts in Henan

Zhenjiang Dong
Polish Journal of Environmental Studies
Remote Sensing and Land Use
article

Integrating Geo-AI with GIS and RSfor Analyzing Land Cover Transformationand Its Impacts in Henan

Zhenjiang Dong
article en

Abstract

Understanding the interaction between land use and land surface temperature (LST) is essential for tackling the increasing problems of urbanization, environmental degradation, and climate change.This research explores the spatial and temporal patterns of Land Use and Land Cover (LULC) and their effect on LST in Henan Province, China, between 1990 and 2024, spanning 34 years.Using multi-temporal Landsat imagery, supervised classification using the Random Forest algorithm, and cloud-based processing in Google Earth Engine (GEE), we have mapped LULC changes and extracted LST values with high spatial resolution and temporal consistency.The findings indicate extensive land transformation, with urban areas increasing by more than 181%, mainly at the cost of cropland, which decreased by almost 11%.Concurrently, LST rose markedly, with maximum surface temperatures increasing from 43.2C to 51.3C.Built-up and barren land exhibited the highest mean LST values, while forests and water bodies consistently recorded cooler temperatures, highlighting the role of vegetative cover and hydrological features in mitigating surface heat.To quantify these relationships, Pearson correlation analysis was performed between the area of each LULC class and its corresponding LST.The results showed significant positive correlations between land built-up and LST (r>0.94), and significant negative correlations for cropland and forest cover (r<-0.95),affirming the urbanization-and land-degradation-related thermal amplification.The research establishes the pivotal relationship between LULC changes and surface thermal trends, providing an actionable geospatial model for environmental monitoring and land management.The incorporation of long-term satellite data with statistical correlation produces actionable information for policymakers, urban planners, and sustainability stakeholders.With Henan and much of the rest of the world continuing to urbanize rapidly, this study reinforces the need to balance development with ecological resilience to reduce increasing surface temperatures and their larger climate impacts.

Polish Journal of Environmental Studies
Palestine Polytechnic University (PS)
Openalex Percentile: Top 69%
Remote Sensing and Land Use
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Integrating Geo-AI with GIS and RSfor Analyzing Land Cover Transformationand Its Impacts in Henan — Zhenjiang Dong · Polish Journal of Environmental Studies (2025) | TGRS Research Map | TGRS