Land Use Map Research Articles

Development of Four Component Scattering Power Decomposition Technique for Dual Polarization SAR Data

AbstractThe increasing availability of dual-polarimetric synthetic aperture radar (PolSAR) data has led to a significant rise in its applications over the past few decades. Model-based decompositions combined with polarimetric information extraction from PolSAR data play a crucial role in target identification and classification. In this context, the covariance matrix [C], composed of four independent parameters, was used as the input for dual-pol four-component scattering power decomposition (DP-4SD). A novel 4SD model was tested using dual polarimetric SAR data from the spaceborne ALOS-2/PALSAR-2, and its performance was evaluated against existing scattering power decomposition methods. The performance of the proposed 4SD model was assessed using dual-polarization data from the Haldwani Forest and San Francisco to evaluate its classification capabilities within a single class (forest) and across various land use and land cover classes in San Francisco. The overall classification accuracy achieved was 85.69% for the Haldwani forest and 93.66% for San Francisco, with fewer unclassified samples compared with the existing model. The 4SD model demonstrates superior classification accuracy and enhances the interpretation of polarimetric information, indicating its potential to significantly improve land-use and land-cover mapping using dual PolSAR data.

A method to map land use impacts on microclimate regulation supply in urban environments

Land use impacts land surface temperature (LST), especially in urban areas where anthropogenic materials have a high capacity to store energy. Nevertheless, cities have many other land uses (e.g., forests, lawns) that can reduce LST and contribute to high microclimate regulation. In this work, we develop a method to map land use impacts on microclimate regulation supply using an Unmanned Aerial Vehicle (UAV). A detailed methodology was developed for 1) UAV's mission planning, 2) field data collection for method validation, 3) RGB and thermal mission reconstruction, 4) land use classification, 5) data extraction and 6) spatial and statistical analysis. The method developed can be beneficial to local authorities and transferable to other realms. It will allow us to understand the impacts of different land uses on microclimate regulation. For this, an area with heterogeneous land uses was used as a test site.• A novel methodology was created to map land use impacts on microclimate regulation supply in urban areas;• High-resolution UAV RGB and thermal imagery for land-use classification and surface temperature analysis;• The method can help understand the capacity of the different land uses on microclimate regulation;

Land use and land cover mapping of the Saco River’s watershed, State of Maranhão, Brazil

Land use and land cover mapping benefits landscape understanding and its changes, especially those resulting from anthropogenic actions in the physical environment. The present study aimed at mapping land use and coverage of the Saco River’s watershed (located in Codó, state of Maranhão). The area comprises the coconut forest (named Mata dos Cocais), a region that encompasses the characteristics of different biomes on the same temporal and spatial scale. The methodology applied was based on remote sensing techniques developed in a Geographic Information System (GIS) environment, processing data from Landsat 8 and supervised classification. The results showed a predominance of dense vegetation in the basin under study, in addition to a reduced occupation by classes of urban area and water bodies. The overall accuracy was 79% and dense vegetation presented a higher user and producer accuracy than the general, with 91 and 87%, respectively. On the other hand, the highest commission and omission errors were those in urban areas and water bodies, which coincided with the lowest occupation classes in the Saco River basin. These results are pioneering for the coconut forest and provide data for strategic planning of environmental actions.

GAMBUT field measurement of emissions from a tropical peatland fire experiment: from ignition to spread to suppression

Background Accurate quantification of emissions from peatland wildfire is crucial for understanding their feedback to the atmospheric and Earth system. However, current knowledge on this topic is limited to a few laboratory and field studies, which report substantial variability in terms of the fire emission factors (EFs). Aims We aim to understand how emissions vary across the life cycle of a peatland fire. Methods In August/September 2018, we conducted the largest and longest to-date field-scale experimental burn on a tropical peatland in Sumatra, Indonesia. Field measurements of gas emissions from the fire experiment were conducted using an open-path Fourier transform infrared spectroscopy to retrieve mole fractions of 11 gas species. Key results For the first time, we calculated and reported EFs from 40 measurement sessions conducted over 2 weeks of burning, encompassing different fire stages (e.g. ignition, smouldering spread, and suppression) and weather events (e.g. rainfall). Our findings provide field evidence to indicate that EFs vary significantly among fire stages and weather events. We also observed that the heterogeneous physicochemical properties of peatland site (e.g. moisture content) influenced the EFs. We also found that modified combustion efficiency was highly sensitive to complex field variables and could introduce large uncertainties when determining the regimes of a peat fire. Conclusions and implications Further studies to investigate peat fire emissions are needed, and more comprehensive mapping of peatland heterogeneity and land use for emissions inventories, accounting for spatial and temporal variability in EFs since the initiation of a fire event is required.

Spatial Analysis of the Impacts Caused by Changes in Land Use on the Estimation of Surface Temperature in the The City of Paracatu (MG)

The increase in built-up areas, coupled with the suppression of vegetation without the necessary mitigating measures to curb the effects of urbanization, causes changes in the microclimate and directly impacts the health of the local population. In this sense, the present study aims to analyze the influence of land cover type on the variation of Land Surface Temperature (LST) estimation in the city of Paracatu, Minas Gerais (MG), in the years 1990 and 2020.For this, the maps provided by the Annual Mapping of Land Cover and Land Use of Brazil (MapBiomas) and images from the LANDSAT-5 (1990) and LANDSAT-8 (2020) satellites were used. Four images, distributed across seasons, were utilized to estimate LST for these periods, aiming to obtain a representative LST estimate for that year. For the calculation of the LST with bands 6 and 10, respectively of the LANDSAT-5 and 8 satellites, the SCP plugin of the QGIS software was used, and the process of recovery of the LST in the scenes used occurred through conversion of the values of the Digital Number (DN) into radiance at the Top of the Atmosphere (ToA), conversion of radiance into brightness temperature in ToA, correction of atmospheric effects and obtaining LST in Kelvin and, subsequently, in degrees Celsius. After that, the average between them was performed by means of normalization of each of the scenes, obtaining a representative mosaic for the LST of each year,thus enabling the estimation of the spatial behavior of the minimum, mean, and maximum values.. Finally, in order to verify the influence of Changes in Use and Occupation (LULC) on the spatial variation of the LST, the classes found in Vegetation, Exposed Soil, Urban Area and Water Resources were segmented, and it was found that, while the urban area of Paracatu had its territorial extension practically doubled, the vegetation class decreased by almost 25%, a fact that implied in the average increase of the LST by more than 5º C. the minimum and maximum values of these classes varied around 4.5 and 3º C, and it is possible to conclude that, in this interval of 30 years, Paracatu had no urban growth occurring exponentially and without the proper mitigations for the transformation of the microclimate, implying the need for measures that can curb these changes in strategic points of the municipality, as in the Bom Pastor neighborhood, which had its use and occupation totally changed in this temporal hiatus. In addition, in view of the estimates of economic growth in the city, it is believed that these measures should be taken as a matter of urgency, so that the results presented here can support the decisions of the managing public agencies.

The application of remote sensing and geographic information system techniques for the analysis of land use and land cover changes in Wayanad district of Kerala

Mapping Land Use and Land cover Changes (LULC) and detecting changes using remote sensing and Geographic Information System (GIS) techniques is a cost-effective way of gaining a good understanding of the land cover alteration processes caused by land use change and their effects. This study assessed the transformation of the Wayanad district landscape over a period of 23 years. LANDSAT satellite images (of 30 m resolution) encompassing the area at three epochs were classified into nine classes (coffee dominated mixed crop, built-up, evergreen forest, deciduous forest, grassland, mixed crop with built-up, paddy, tea plantation, and waterbody) using the maximum likelihood algorithm, resulting in classes for each land use. The results showed that over the past 23 years, coffee-dominated mixed crops have increased by 0.84% in 2014 and 11.84% in 2022 compared to 1999; deciduous forest area decreased 3.6% and increased 0.6% in 2014 and 2022, respectively. Tea plantations increased by 0.9% in 2014 and by 0.49% in 2022, which decreased by 0.41% compared to 2014. Built-up has increased by 6.42% and 6.02% in 2014 and 2022 respectively, and slightly decreased by 0.4% compared to 2014. Evergreen forest areas increased in 2014 by 6.68% and 2.28% in 2022 and decreased by 4.44% compared to the previous time period. Grass land areas have decreased by 6.25% and 5.33%, respectively, and mixed crops with built-up areas has decreased by 0.74% and remained the same in the last two epochs, while paddy and waterbodies have decreased by 3.4%, 15.79%, and 0.07 and 0.19%, respectively, in 2014 and 2022 of the total geographical area Keywords: Remote sensing, GIS techniques, LULC, forest cover

Spatial Anaysis and Modelling to Mappping Priorities Areas for Restauration: Study Case: Natural Protected Area Montes Azules, Chiapas, Mexico

Natural Protected Areas play a fundamental role in the conservation of biodiversity and ecosystems throughout the world and are designated and managed with the purpose of preserving biological and cultural capital, ensuring the sustainable use of natural resources, and maintaining ecosystem services. The Montes Azules Biosphere Reserve, like other Natural Protected in Mexico, faces significant challenges such as deforestation, illegal logging, and loss of vegetation cover, as well as socio-environmental conflicts, factors that hinder the biological and cultural conservation of the area. Likewise, despite their importance, many Natural Protected face significant challenges in terms of effective monitoring and planning. The lack of adequate monitoring and planning strategies, as well as staff and budget, makes it difficult to assess the conservation status of these areas and to implement appropriate management measures. Therefore, creating specific monitoring tools is essential to periodically evaluate their conservation status and identify threats and pressures on ecosystems in order to design adaptive and effective management strategies. The objective of this study is to offer a first methodological approach to identify priority areas for restoration within the Montes Azules Biosphere Reserve, which will allow decision-makers to design and apply conservation strategies in the area. The determination of the priority areas for restoration was based on an environmental management process, where the Land suitability is the base for the territorial arrangement, which was modeled together with the current land use and land cover through rules of decision and having the natural protected area as a frame. For land suitability, the land classification system was used according to its use capacity or American system of the 8 classes developed by the Soil Conservation Service of the United States; for mapping land use land cover, an object base classification method was used. The total transformed area in 2023 occupies an extension of 39,475.38 ha, approximately 50% of this lands corresponds to sloping and very steep land and in some cases with shallow to very shallow soils, not suitable for agriculture. The area identified as priority zones for restoration corresponds to an extension of 19,514.5 ha, which represents nearly 50% of the transformed area, and 6% of the total of study area, from which 6,860.5 ha are top priority for restoration. As main conclusion can be said that the methodological proposal described here serves as a first approximation to identify priority zones for restoration in the Montes Azules Biosphere Reserve, allowing for a more detailed identification of these areas at the local level, which will allow decision-makers to design and apply conservation strategies in the area.

Andean Landscape Legacies: Comprehensive Remote Sensing Mapping and GIS Analysis of Long-Term Settlement and Land Use for Sustainable Futures (NW Argentina)

The Andes region has an exceptional record of high-altitude settlements integrated within widespread regional chains of mobility and exchange. The Sierra de Aconquija (NW Argentina, south-central Andes) is an effective climatic barrier that has afforded an enduring indigenous approach to land use, mobility, and exchange over millennia. Despite this rich history, the Sierra has been largely considered marginal in pre-Columbian regional cultural developments. Today, the expansion of extractive industries threatens the region’s heritage and the sustainable futures of local communities. Innovative, integrative methodologies are needed for landscape characterisation, heritage assessment, and sustainable policy development. Building on earlier work, we undertook the first comprehensive mapping of archaeological features over 3800 sq. km of the Sierra using interpreter-led assessment of commercial and open-access satellite imagery and DSM data, to verify earlier assumptions and to identify previously unnoticed trends in the aggregation, distribution, and connectivity of archaeological features. The mapping identified 6794 features distributed unevenly but with clear tendencies towards maximising topographic, ecologic, and connectivity advantages expressed consistently across the study area. The outcomes confirm the important role the Sierra had in pre-Hispanic times, highlighting the significance of ancient indigenous practices for the sustainability of vulnerable upland landscapes both in the Andes and worldwide.

Reviews on the Land Use and Land Cover Changes in Bangkok

Remote sensing has been a highly effective and efficient method for spatial and socio-political analyses for several decades. It utilizes satellite images to map land use and land cover (LULC) and detect changes in this regard. One of Southeast Asia’s megacities, Bangkok has undergone significant land use dynamics and related socioeconomic activity changes. Recently, the new Land and Buildings Tax Act B.E. 2562 (A.D. 2019) has been implemented, which could impact land-use changes, particularly in vacant lands. This study aims to review the literature on LULC changes in Bangkok since the implementation of the land tax and to provide a summary of the main findings. The reviews indicate that previous literature on LULC in Bangkok has primarily focused on environmental or spatial factors, rather than socio-economic ones. This highlights a gap in our understanding of the socio-economic and LULC impacts of land taxation.

Assessing Future hydrological response of an urban watershed using machine learning based LULC forecasting models

Urbanization in terms of land-use/cover (LULC) change has a long-term significant impact on the hydrological cycle as the LULC is one of the most important influencing parameters to produce curve number (CN). The drastic change in LULC changes the CN. This change directly affects surface water including peak flows. This study aims to assess the change in surface runoff due to changes in LULC. Hydrological modeling is done for the consistent long-term behavioral study of surface runoff. The area focused on the study is the Kharun river, a tributary of the Mahanadi River. For the assessment of the impact of LULC change on the catchment discharge, a daily-step conceptual model soil and water assessment tool (SWAT) was applied. Landuse maps were prepared with the Landsat Thematic Mapper satellite images. The future land use was forecasted with the technique of spatial statistical modeling. The machine learning (ML) tool is used for quantifying the influences on the LULC change dynamics and producing the LULC map for 2024 and 2030. Remote sensing (RS) and geographic information system (GIS) analysis were coupled with hydrological SWAT modeling to investigate the connection between the LULC change and hydrologic regime. The SWAT Model’s calibration efficiency is verified by comparing the simulated and observed discharge time series at the Patharidih gauge and discharge station. The monthly and daily calibrations were quite satisfactory, with Nash-Sutcliffe an efficiency coefficient of 0.86 and 0.67. This modeling provides reliable information for sustainable management of available water resources of the catchment.

Bioretention as a control to urban drainage system with an ecohydrological base: GIS as a tool on decision making

ABSTRACT The occupation and use of urban land has made it difficult for water to infiltrate and, consequently, the volume of runoff in cities has increased, which has made the development of bioretention techniques in the field of hydrology essential. This study aims to define and apply criteria for identifying areas for constructing bioretention systems and conducting evaluations based on Geographic Information System indicators, considering quantity and quality in urban drainage. The developed method allows users to verify and compare changes in the surface of urban areas and their interference with the local environment, to map land use and occupation to simplify procedures for defining and prioritizing areas for the construction of bioretention systems and to utilize resources from georeferenced bases to resolve eco-hydrological issues. The study develops technical bases for using a tool to analyze areas with speed and consistency as a foundation for decisions on implementing bioretention systems.

Estimation of Runoff at Shetrunji River Basin using SWAT Hydrological Modelling

The researchers and scientists have realized that this is the high time to act in accordance to the impact of change of climate. Because of climate change problem, various effects occur, one of them is hydrological extremes. This leads to the emergence of hot-spots and vulnerable areas causing difficult adaptation. The current analysis intends to estimate the influence of change in climate on the hydrological parameter on one of the most important tributaries of Saurashtra region of Gujarat, Western India. Out of number of methods available to perform this task, simulation (hydrological modelling) which is the most widely used techniques available at this time, has been adopted. Here in this research the SWAT (Soil and Water Assessment Tool) model which happens to be a semi-distributed model and integrates the GIS information with the attribute database of the River has been utilized. The watershed delineation has been done using AWD (Automatic Watershed Delineation) which is available as a plugin in ArcSWAT. It has classified the catchment into 28 subbasins. From Esri Sentinel-2 landuse map has been used and the soil map is extracted from FAO Raster world soil map. Moreover, we can classify the sub basins into 173 HRUs (Hydrological Response Unit) by the model. The weather files from 1982 to 2019 has been used from the global weather source as a seed to the model. The successful run of the model gives elucidate fluctuating runoff volumes over time, spanning from a lowest of 2.56 mm to a extreme of 503.78mm. Notably, the annual average runoff stands at 190.82 mm, representing approximately 28.34% of the cumulative rainfall experienced within the river basin. The estimation of runoff is helpful in allocating water for agriculture, household demands, and industrial requirements.

Contribution of Landsat Multispectral Images to the Land Cover Dynamics of the Toéghin-Bangré Watershed for the Period 1998 to 2022 in Burkina Faso

Remote sensing plays an important role in the continuous observation of the earth's surface. It produces large databases that can be used to map and monitor natural resources. To this end, land-use maps are genuine planning and decision-making tools for natural resource management. The aim of this study is to use remote sensing products to show the dynamics of land use, to understand these dynamics and their impact on water resources in general and on hydrology in particular. Specifically, it is a question of identifying the similarities and differences that have occurred, and finally evaluating the rate of change. The methodology adopted is the use of the likelihood algorithm to produce three thematic classifications for the years 1998, 2010 and 2022. Overall accuracy is determined from the confusion matrix, which ranges from 80% to 91%. Supervised classification yielded seven occupancy classes: water bodies, cultivated areas, gallery forests, habitats/outcrops, grassy savannahs, wooded savannahs and bare ground. Quantification of change from 1998 to 2022, assessed by the rate of change (Tc), shows a progressive trend estimated at 31.82% (habitats/outcrops) and 43.40% (grassy savannah), and a regressive trend estimated at -17.92% (cultivated areas); -95.15% (gallery forests); -51.93% (water bodies) and -78.36% (bare ground). At the end of our study, diachronic analysis enabled us to quantify changes between the years 1998-2010, 2010-2022 and overall 1998-2022 with good precision.

Discerning the dynamics of urbanization-climate change-flood risk nexus in densely populated urban mega cities: An appraisal of efficient flood management through spatiotemporal and geostatistical rainfall analysis and hydrodynamic modeling

While the contribution of climate change towards intensifying urban flood risks is well acknowledged, the role of urbanization is less known. The present study, for the first time in flood management literature, explores whether and how unplanned-cum-urbanization may overshadow the contribution of extreme rainfall to flood impacts in densely populated urban regions. To establish this hypothesis and exemplify our proposed framework, the National Capital Territory (NCT) of Delhi in India, infamous for its concurrent flood episodes is selected. The study categorically explores whether the catastrophic 2023 urban flood could have resulted in a similar degree of urban exposure and damage, had it occurred anytime in the past. A comprehensive spatiotemporal and geo-statistical analysis of rainfall over 11 stations brought about through Innovative trend analysis, Omnidirectional and directional Semi-variogram analysis, and Gini Index indicates a rise in extreme rainfalls. High-resolution land-use maps indicate about 39.53 %, 52.66 %, 56.60 %, and 69.18 % of urban footprints during 1993, 2003, 2013, and 2023, while gradient direction maps indicate a prominent urban surge towards the North-West, West, and Southwest corridors. A closer inspection of the Greenness and Urbanity indices reveals a gradual decline in the green footprints and concurrent escalation in the urban footprints over the decades. A 3-way coupled MIKE+ model was set up to replicate the July 2023 flood event; indicating about 13 % of the area experience “high” and “very-high” flood hazards. By overlaying the flood inundation and hazard maps over land-use maps for 1993, 2003, and 2013, we further establish that a similar flood event would have resulted in lesser damage and building exposure. The study offers a set of flood management options for refurbishing resilience and limiting flood risks. The study delivers critical insights into the existing urban flood management strategies while delving into the urban growth-climate change-flood risk nexus.

A novel hybrid methodology integrating pixel- and object-based techniques for mapping land use and land cover from high-resolution satellite data

ABSTRACT The classification of very high-resolution satellite imagery remains a focal point in remote sensing, attracting increased attention across diverse scientific disciplines. Various classification methods, including pixel- and object-based techniques, have been proposed, and their performances and limitations have been discussed in the literature. This paper presents a hybrid method that combines the strengths of pixel- and object-based methods in image classification to minimize errors associated with the segmentation process, particularly under-segmentation errors in object-based image analysis. The core concept behind the method lies in categorizing segmented image objects as either homogeneous or heterogeneous based on their class probability. In this process, the estimated possibilities from the object-based classification model are considered, and segments are designated as homogeneous or heterogeneous using a user-defined threshold. The object-based classification model determines the class labels for homogeneous image objects, while the heterogeneous ones, containing pixels representing different land cover classes, are classified using the pixel-based model. The performance of hybrid classification models, created by varying thresholds, is analysed using high-resolution WorldView-3 and WorldView-2 imagery and compared with pixel- and object-based classification results. For the implementation of image classification methods, Canonical Correlation Forest (CCF), Extreme Gradient Boosting (XGBoost), and Categorical Boosting (CatBoost) were employed. The findings indicated that employing the suggested hybrid strategy with a threshold value selected within a specific range (e.g. between 60% and 80%) and employing a robust classification algorithm that provides class probabilities (e.g. CCF) results in a statistically significant improvement in overall accuracy compared to pixel and object-based methods, with gains of 5% and 4%, respectively. Visual analysis of the produced thematic maps revealed that the proposed method minimizes the salt-and-pepper effect associated with pixel-based classification while mitigating segmentation problems arising from object-based classification.

Mapping Vegetation Types and Land Use Dynamics in Kanyabaha Wetland from 1990 to 2021

Wetlands are crucial ecosystems providing essential ecological services, yet they face increasing threats from human activities. This study focuses on Kanyabaha Wetland in Uganda, examining its vegetation dynamics over three decades (1990-2021) using Landsat satellite imagery. The research characterizes land use and cover types including papyrus, grasslands, farmlands, tree plantations, built-up areas, and woodlands. Remote sensing data was processed and classified using ArcMap software, validated through field verification, resulting in high overall accuracy (>75%) across all study years. The images were analyzed using a hybrid of unsupervised (ISO data) and supervised (Maximum Likelihood) classification techniques. Findings reveal significant shifts in vegetation cover, with papyrus dominating initially but declining over time due to expansion in farmlands and settlements. Grasslands also decreased, while areas under farming and built-up structures expanded. Transition matrices illustrate these changes, highlighting stable and shifting landscape dynamics. Statistical analyses indicate a decrease in papyrus cover from 51.5% in 1990 to 39.1% in 2021, while farmland and built-up areas increased from 3.0% to 31.6% and 3.2% to 5.1%, respectively. This study highlights the vulnerability of Kanyabaha Wetland to anthropogenic impacts, necessitating targeted conservation strategies to sustain its ecological integrity amid ongoing land use changes.

Análise sobre o uso da terra no município de Gandu, Baixo Sul Baiano: Interação da cultura cacaueira com o bioma de Mata Atlântica

The present research aims to analyze the land use in the municipality of Gandu, in the Southern Bahian Lowlands, and the interaction of the cocoa crop with the Atlantic Forest biome. As a methodology, theoretical and empirical surveys were carried out on phytophysiognomic diversity, land use and some species of the Atlantic Forest biome, as well as their agroecological relationship with cocoa crop. Interviews were made and questionnaires were applied on the relationship between cocoa production and the forest, field visits to cocoa farms, photographs of the forest (camera), cocoa cultivation in the municipality and also the identification of species with greater incidence in the landscape, use of the GIS (Geographic Information System) system as a geographic database for the analysis of geospatial data and generation of a map of location and land use. The results obtained reveal that most of the interviewees say that there has been degradation in the vegetation cover of the biome in recent decades, the vast majority say that the preservation of the forest is associated with the cultivation of cocoa, and that without it, the devastation of the forest was greater for the implementation of other crops such as cattle raising, bananas and subsistence crops at the time of the witches' broom. The fieldwork, together with the satellite images, shows that the forest is quite altered and this is associated with the use of the land: called capoeirinha, capoeira and capoeirão and more or less preserved fragments of the native ombrophilous forest in mountainous areas. It is concluded that the crop relationship is the most recurrent and oldest land use practice in the municipality of Gandu-Ba and that even with the changes in the dense ombrophilous forest, the cocoa crop contributes to the conservation of the Atlantic Forest biome through its Agroforestry System (AFS) that conserves part of the forest for exotic shading.

Broadening the horizon in land use change modelling: Normative scenarios for nature positive futures in Switzerland

Within scenario-based research of social-ecological systems, there has been a growing recognition of the importance of normative scenarios that define positive outcomes for both nature and society. While several frameworks exist to guide the co-creation of normative scenario narratives, examples of operationalizing these narratives in quantitative simulation modelling are still limited. To address this gap, this paper presents an example of how aspects of normative scenarios can be realized within a spatial model of land use and land cover change. This is achieved through a combination of data-driven approaches to encapsulate scenario-specific differences in local and global scale phenomena, as well as iterative expert elicitation to quantify descriptive trends from narratives. This approach is demonstrated with a case study simulating five scenarios of landscape change (three normative and two exploratory) in Switzerland between 2020 and 2060. The resulting maps of future land use and land cover exhibited distinct variations between the scenarios, notably with regard to the prevalence of areas of heterogeneous semi-natural land, such as alpine pastures and grassland, often considered culturally emblematic of Switzerland. While the simulation results were generally consistent with the outcomes expressed in the scenario narratives, following a process of expert feedback, we reflect that there are clear challenges in leveraging such results to elicit further discussions as to the desirability and plausibility of future scenarios. Specifically, the need to summarize spatial simulations in a manner that is easily interpretable and encourages consideration of the broader patterns of change rather than focusing on fine-scale details.

Multi-Tier Land Use and Land Cover Mapping Framework and Its Application in Urbanization Analysis in Three African Countries

The population of Africa is expected to rise to 2.5 billion by 2050, with more than 80% of this increase concentrated in cities. Africa’s anticipated population growth has serious implications for urban resource utilization and management, necessitating multi-level monitoring efforts that can inform planning and decision-making. Commonly, broad extent (e.g., country level) urban change analyses only examine a homogenous “developed” or “built-up” area, which may not capture patterns influenced by the heterogeneity of landscape features within urban areas. Contrarily, studies examining landscape heterogeneity at a finer resolution are typically limited in spatial extent (e.g., single city level). The goal of this study was to develop and test a hierarchical integrated mapping framework using globally available Earth Observation data (e.g., Landsat, Sentinel-2, Sentinel-1, and nightlight imagery) and accessible methodologies to produce national-level land use (LU) and urban-level land cover (LC) map products which may support a range of global and local monitoring and planning initiatives. We test our multi-tier methodology across three rapidly urbanizing African countries for the 2016–2020 period: Ethiopia, Nigeria, and South Africa. The initial output of our methodology includes annual national land use maps (Tier 1) for the purpose of delineating the dynamic boundaries of individual urban areas and monitoring national LU change. To complement Tier 1 LU maps, we detailed urban heterogeneity through LC classifications within urban areas (Tier 2) delineated using Tier 1 LU maps. Based on country-optimized sets of selected features that leverage spatial/texture and temporal dimensions of available data, we obtained an overall map accuracy of between 65 and 80% for Tier 1 maps and between 60 and 80% for Tier 2 maps, dependent on the evaluation country, although with consistent performance across study years providing a solid foundation for monitoring changes. We demonstrate the potential applications for our products through various analyses, including urbanization-driven LU change, and examine LC urban patterns across the three African study countries. While our findings allude to general differences in urban patterns across national scales, further analyses are needed to better understand the complex drivers behind urban LC configurations and their change patterns across different countries, city sizes, and rates of urbanization. Our multi-tier mapping framework is a viable strategy for producing harmonious, multi-level LULC products in developing countries using publicly available data and methodologies, which can serve as a basis for a wide range of informative and insightful monitoring analyses.

Enhancing Forest‐Steppe Ecotone Mapping Accuracy through Synthetic ApertureRadar‐Optical Remote Sensing Data Fusion and Object-based Analysis

In ecologically vulnerable regions with intricate land use dynamics, such as ecotones, frequent and intense land use transitions unfold. Therefore, the precise and timely mapping of land use becomes imperative. With that goal, by using principal component analysis, we integrated Sentinel-1 and Sentinel-2 data, using an object-oriented methodology to craft a 10-meter-resolution land use map for the forest‐grassland ecological zone of the Greater Khingan Mountains spanning the years 2019 to 2021. Our research reveals a substantial enhancement in classification accuracy achieved through the integration of synthetic aperture radar‐optical remote sensing data. Notably, our products outperformed other land use/land cover data sets, excelling particularly in delineating intricate riverine wetlands. The 10-meter land use product stands as a pivotal guide, offering indispensable support for sustainable development, ecological assessment, and conservation endeavors in the Greater Khingan Mountains region.