Remote Sensing and GIS for Monitoring Land Use Change and Its Ecological Effects—2nd Edition

Topic Information

Dear Colleagues,

Land-use change (LUC) is a cause and result of global changes in the environment. It provides essential food, feed, fuel, and ecosystem services for human social systems, while increasingly affecting the biogeochemical processes of the Earth, such as material exchange, energy balance, the carbon and water cycles, and climate change. In the current “Anthropocene” era, land use has undergone unprecedented changes and intensification to meet the demands of the growing population for goods and services, and has had negative impacts in terms of deforestation, land degradation, habitat reduction, biodiversity loss, non-point source pollution, and greenhouse gas emissions. In order to alleviate these negative impacts and improve the efficiency and sustainability of land use, it is essential to optimize its structure, functions, and patterns. To achieve this goal, remote sensing (RS) and geographic information systems (GISs) can provide large-scale, real-time, accurate, and consistent ground information, as well as the high-performance capability to compute, analyze, and display multi-source data. These technologies have been widely used in monitoring LUC and its ecological effects; therefore, it is imperative to integrate RS and GISs to reveal the spatiotemporal processes, driving mechanisms, multi-functions, and optimization patterns of LUC. This will support the scientific basis and practical implications necessary for sustainable land-use planning, environmental quality improvements, and coordinated human–Earth system developments.

The aim of this Topic is to advance novel theories and methods that contribute new knowledge on various aspects of LUC. Specifically, this Topic seeks to (1) monitor the spatiotemporal patterns and processes of typical LUCs, including cropland reclamation and abandonment, crop type adjustment, rural construction and restructure, urban sprawl and compactness, and ecological land protection; (2) reveal the coupled natural and anthropogenic driving mechanisms of LUC; (3) quantify the various aspects associated with LUC, such as economic benefits, resident livelihoods, food production, agricultural non-point source pollution, ecosystem services, and ecological risks, and analyze their trade-offs and synergies; (4) assess the vulnerability, resilience, and sustainability of different land-use patterns in the human–Earth system; and (5) simulate as well as optimize LUC under different development scenarios to create adaptation strategies for future challenges. The original research articles and reviews presented in this Topic will offer scientific methodologies, systematic insights, and policy recommendations for effective land-use management and regional sustainable development. By addressing these critical themes of LUC, this Topic will contribute to the advancement of knowledge and provide practical guidance for stakeholders and policymakers seeking to optimize land use for the benefits of society and the environment.

We look forward to receiving your submissions.

Dr. Yaqun Liu
Dr. Wei Song
Prof. Dr. Jieyong Wang
Dr. Kangwen Zhu
Dr. Xuanchang Zhang
Dr. Cong Ou
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Agronomy agronomy	3.4	6.7	2011	17 Days	CHF 2600	Submit
Remote Sensing remotesensing	4.1	8.6	2009	24.3 Days	CHF 2700	Submit
Urban Science urbansci	2.9	3.7	2017	21.6 Days	CHF 1800	Submit

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20 pages, 3112 KB  

Open AccessArticle

A Causal Remote Sensing Framework to Disentangle Climate and Anthropogenic Drivers of Grassland Recovery on the Qinghai–Tibet Plateau

by Zhenghe Liu, Erfu Dai, Shuo Xing, Liang Zhou and Hong Gao

Remote Sens. 2026, 18(3), 504; https://doi.org/10.3390/rs18030504 - 4 Feb 2026

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Abstract

Disentangling the impacts of ecological restoration from climate change is an ongoing challenge in remote sensing since the traditional correlative approaches often cannot elucidate causal mechanisms. To overcome this, we introduce a Causal Remote Sensing Framework that uses multi-source satellite data (2000–2020), machine [...] Read more.

Disentangling the impacts of ecological restoration from climate change is an ongoing challenge in remote sensing since the traditional correlative approaches often cannot elucidate causal mechanisms. To overcome this, we introduce a Causal Remote Sensing Framework that uses multi-source satellite data (2000–2020), machine learning (XGBoost, SHAP) and causal inference (T-Learner) to build pixel-level counterfactuals. Using this framework, we assessed the Return Grazing to Grassland Program (RGGP) on the Qinghai–Tibet Plateau. Our results demonstrate that a warming and wetting climate improved Water yield (WY) while at the same time decreasing sand fixation (SF) in 83.6% of the region. Notably, the restoration project became the main factor that slowed this decline. After controlling for observational selection bias, the program had a net positive effect of (+6.02 t hm⁻²), reducing degradation in 64.6% of treated areas. This framework provides a practical way for the remote sensing community to go beyond change monitoring to allow the diagnosis of the causal mechanisms in complex human-environment systems. Full article

(This article belongs to the Topic Remote Sensing and GIS for Monitoring Land Use Change and Its Ecological Effects—2nd Edition)

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20 pages, 8812 KB  

Open AccessArticle

Spatiotemporal Analysis of Thermal Environment and Land Use Change in Sonipat, Panipat, and Jhajjar Districts Under the Central Circle Forest Area of Haryana, India (1993–2023)

by Himanshi Sharma, Doyeli Sanyal, Rishikesh Singh and Santosh Pal Singh

Urban Sci. 2026, 10(2), 95; https://doi.org/10.3390/urbansci10020095 - 3 Feb 2026

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Abstract

Changes in land use patterns due to urbanisation impact local weather patterns by influencing Land Surface Temperatures (LSTs). Despite rapid urbanisation in the Delhi-NCR (National Capital Region), the peri-urban fringes of Haryana, such as the Central Circle Forest (CCF) region, in the past [...] Read more.

Changes in land use patterns due to urbanisation impact local weather patterns by influencing Land Surface Temperatures (LSTs). Despite rapid urbanisation in the Delhi-NCR (National Capital Region), the peri-urban fringes of Haryana, such as the Central Circle Forest (CCF) region, in the past three decades, a comprehensive 30-year analysis that integrates LST, the Normalised Difference Vegetation Index (NDVI), the Normalised Difference Built-up Index (NDBI), and Land Use/Land Cover (LULC) is lacking. The current study on the decadal analysis covering the 1993 to 2023 time period shows an increase in built-up areas (14.6–38.4%), a decline in NDVI (−0.01 to −0.08), a 6 °C rise in summer LST, and weak correlations between LST and NDVI. A significant increase in summer mean LSTs was observed, with some regions reaching temperatures beyond 35 °C in the selected districts. The LST and LULC zonal statistics revealed that the open fields/agricultural land and floodplains of the Yamuna River have adversely affected the weather pattern with rising LST. The average NDVI declined from −0.01 in 1993 to −0.08 in 2023, indicating a loss of vegetative buffers. Meanwhile, NDBI trends from 2003 to 2023 showed that built-up areas have steadily grown, and LULC data highlighted 38.43% of the built-up area in 2023. Correlation analysis showed a weak negative relationship between LST and NDVI (r = −0.47), suggesting diminishing cooling effects of vegetation, while a weak positive correlation between LST and NDBI indicates that urban expansion is significantly contributing to the urban heat island effect. This study emphasises the need for green infrastructure, afforestation, and water conservation in urban planning frameworks to enhance climate resilience and ecological sustainability. Full article

(This article belongs to the Topic Remote Sensing and GIS for Monitoring Land Use Change and Its Ecological Effects—2nd Edition)

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23 pages, 9870 KB  

Open AccessArticle

Transition Characteristics and Drivers of Land Use Functions in the Resource-Based Region: A Case Study of Shenmu City, China

by Chao Lei, Martin Phillips and Xuan Li

Urban Sci. 2025, 9(12), 520; https://doi.org/10.3390/urbansci9120520 - 7 Dec 2025

Viewed by 540

Abstract

Resource-based regions play an indispensable role as strategic bases for national energy and raw material supply in the global industrialization and urbanization process. However, intensive and large-scale natural resource exploitation—particularly mineral extraction—often triggers dramatic land use/cover changes, leading to a series of problems [...] Read more.

Resource-based regions play an indispensable role as strategic bases for national energy and raw material supply in the global industrialization and urbanization process. However, intensive and large-scale natural resource exploitation—particularly mineral extraction—often triggers dramatic land use/cover changes, leading to a series of problems including cultivated land degradation, ecological function deterioration, and human settlement environment degradation. However, a systematic understanding of the functional transitions within the land use system and their drivers in such regions remains limited. This study takes Shenmu City, a typical resource-based city in the ecologically vulnerable Loess Plateau, as a case study to systematically analyze the transition characteristics and driving mechanisms of land use functions from 2000 to 2020. By constructing an integrated “element–structure–function” analytical framework and employing a suite of methods, including land use transfer matrix, Spearman correlation analysis, and random forest with SHAP interpretation, we reveal the complex spatiotemporal evolution patterns of production–living–ecological functions and their interactions. The results demonstrate that Shenmu City has undergone rapid land use transformation, with the total transition area increasing from 27,394.11 ha during 2000–2010 to 43,890.21 ha during 2010–2020. Grassland served as the primary transition source, accounting for 66.5% of the total transition area, while artificial surfaces became the main transition destination, receiving 38.6% of the transferred area. The human footprint index (SHAP importance: 4.011) and precipitation (2.025) emerged as the dominant factors driving land use functional transitions. Functional interactions exhibited dynamic changes, with synergistic relationships predominating but showing signs of weakening in later periods. The findings provide scientific evidence and a transferable analytical framework for territorial space optimization and ecological restoration management not only in Shenmu but also in analogous resource-based regions facing similar development–environment conflicts. Full article

(This article belongs to the Topic Remote Sensing and GIS for Monitoring Land Use Change and Its Ecological Effects—2nd Edition)

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