Proportion Of Land Cover Types Research Articles

Regional Accuracy Assessment of 30-Meter GLC_FCS30, GlobeLand30, and CLCD Products: A Case Study in Xinjiang Area

With the development of remote sensing technology, a number of fine-resolution (30-m) global/national land cover (LC) products have been developed. However, accuracy assessments for the developed LC products are commonly conducted at global and national scales. Due to the limited availability of representative validation observations and reference data, knowledge relating to the accuracy and applicability of existing LC products on a regional scale is limited. Since Xinjiang, China, exhibits diverse surface cover and fragmented urban landscapes, existing LC products generally have high classification uncertainty in this region. This makes Xinjiang suitable for assessing the accuracy and consistency of exiting fine-resolution land cover products. In order to improve knowledge of the accuracy of existing fine-resolution LC products at the regional scale, Xinjiang province was selected as the case area. First, we employed an equal-area stratified random sampling approach with climate, population density, and landscape heterogeneity information as constraints, along with the hexagonal discrete global grid system (HDGGS) as basic sampling grids to develop a high-density land cover validation dataset for Xinjiang (HDLV-XJ) in 2020. This is the first publicly available regionally high-density validation dataset that can support analysis at a regional scale, comprising a total of 20,932 validation samples. Then, based on the generated HDLV-XJ dataset, the accuracies and consistency among three widely used 30-m LC products, GLC_FCS30, GlobeLand30, and CLCD, were quantitatively evaluated. The results indicated that the CLC_FCS30 exhibited the highest overall accuracy (88.10%) in Xinjiang, followed by GlobeLand30 (with an overall accuracy of 83.58%) and CLCD (81.57%). Moreover, through a comprehensive analysis of the relationship between different environmental conditions and land cover product performance, we found that GlobeLand30 performed best in regions with high landscape fragmentation, while GLC_FCS30 stood out as the most outstanding product in areas with uneven proportions of land cover types. Our study provides a novel insight into the suitability of these three widely-used LC products under various environmental conditions. The findings and dataset can provide valuable insights for the application of existing LC products in different environment conditions, offering insights into their accuracies and limitations.

Uncertainty Analysis of Multisource Land Cover Products in China

Satellite-based land cover products play a crucial role in sustainability. There are several types of land cover products, such as qualitative products with discrete classes, semiquantitative products with several classes at a predetermined ratio, and quantitative products with land cover fractions. The proportions of land cover types in the grids with coarse resolution should be considered when used at the regional scale (e.g., modeling and remote sensing inversion). However, uncertainty, which varies with spatial distribution and resolution, needs to be studied further. This study used MCD12, ESA CCI, and MEaSURES VCF land cover data as indicators of qualitative, semiquantitative, and quantitative products, respectively, to explore the uncertainty of multisource land cover data. The methods of maximum area aggregation, deviation analysis, and least squares regression were used to investigate spatiotemporal changes in forests and nontree vegetation at diverse pixel resolutions across China. The results showed that the average difference in forest coverage for the three products was 8%, and the average deviation was 11.2%. For forest cover, the VCF and ESA CCI exhibited high consistency. For nontree vegetation, the ESA CCI and MODIS exhibited the lowest differences. The overall uncertainty in the temporal and spatial changes of the three products was relatively small, but there were significant differences in local areas (e.g., southeastern hills). Notably, as the spatial resolution decreased, the three products’ uncertainty decreased, and the resolution of 0.1° was the inflection point of consistency.

Evaluating the Relationships between Riparian Land Cover Characteristics and Biological Integrity of Streams Using Random Forest Algorithms.

The relationships between land cover characteristics in riparian areas and the biological integrity of rivers and streams are critical in riparian area management decision-making. This study aims to evaluate such relationships using the Trophic Diatom Index (TDI), Benthic Macroinvertebrate Index (BMI), Fish Assessment Index (FAI), and random forest regression, which can capture nonlinear and complex relationships with limited training datasets. Our results indicate that the proportions of land cover types in riparian areas, including urban, agricultural, and forested areas, have greater impacts on the biological communities in streams than those offered by land cover spatial patterns. The proportion of forests in riparian areas has the greatest influence on the biological integrity of streams. Partial dependence plots indicate that the biological integrity of streams gradually improves until the proportion of riparian forest areas reach about 60%; it rapidly decreases until riparian urban areas reach 25%, and declines significantly when the riparian agricultural area ranges from 20% to 40%. Overall, this study highlights the importance of riparian forests in the planning, restoration, and management of streams, and suggests that partial dependence plots may serve to provide insightful quantitative criteria for defining specific objectives that managers and decision-makers can use to improve stream conditions.

Multi-scale response of wetland bird assemblages to landscape patterns on a Neotropical island: when wetland type matters more than size

Understanding wetland bird responses to landscape patterns is central for wetland management and bird conservation. This is particularly relevant on islands, where most of the global extinctions have occurred. In this study, we identified landscape patterns in wetlands on Cozumel Island that best explained abundance of birds grouped in 13 trophic guilds at 3 spatial scales (145, 300, and 850 m radius from count points). By using ordination techniques and generalized linear models we found a scale dependent dissimilarity between the use of extensive estuarine and small inland brackish wetlands. At finer spatial scales, abundance of birds in trophic guilds that mainly use estuarine or inland brackish wetlands was associated with the proportion of land cover types of the corresponding wetland type, whereas at the broadest spatial scale, connectivity of such land cover types was more important. Abundance of birds in trophic guilds that do not prefer any particular type of wetland did not show any relationship with landscape diversity nor connectivity of land cover types, but their abundance showed relationships with specific land cover types from both estuarine and inland brackish wetlands as well as with bordering wetland vegetation. We concluded that the presence of continuous extents of land cover types of both extensive estuarine and small inland brackish wetlands are important for the conservation of distinct wetland bird assemblages on Cozumel Island.

Occurrence Prediction of the Citrus Flatid Planthopper (Metcalfa pruinosa (Say, 1830)) in South Korea Using a Random Forest Model

Invasive species cause a severe impact on existing ecosystems. The citrus flatid planthopper (CFP; Metcalfa pruinosa (Say, 1830)) is an invasive species in many countries. Predicting potential occurrence areas of the species related to environmental conditions is important for effective forest ecosystem management. In this study, we evaluated the occurrence patterns of the CFP and predicted its potential occurrence areas in South Korea using a random forest model for a hazard rating of forests considering meteorological and landscape variables. We obtained the occurrence data of the CFP in South Korea from literature and government documents and extracted seven environmental variables (altitude, slope, distance to road (geographical), annual mean temperature, minimum temperature in January, maximum temperature in July, and annual precipitation (meteorological)) and the proportion of land cover types across seven categories (urban, agriculture, forest, grassland, wetland, barren, and water) at each occurrence site from digital maps using a Geographic Information System. The CFP occurrence areas were mostly located at low altitudes, near roads and urbanized areas. Our prediction model also supported these results. The CFP has a high potential to be distributed over the whole of South Korea, excluding high mountainous areas. Finally, factors related to human activities, such as roads and urbanization, strongly influence the occurrence and dispersal of the CFP. Therefore, we propose that these factors should be considered carefully in monitoring and surveillance programs for the CFP and other invasive species.

Spatial Pattern Consistency among Different Remote-Sensing Land Cover Datasets: A Case Study in Northern Laos

Comparisons of the accuracy and consistency of different remote-sensing land cover datasets are important for the rational application of multi-source land cover datasets to regional development, or to studies of global or local environmental change. Existing comparisons of accuracy or spatial consistency among land cover datasets primarily use confusion or transfer matrices and focus on the type and area consistency of land cover. However, less attention has been paid to the consistency of spatial patterns, and quantitative analyses of spatial pattern consistency are rare. However, when proportions of land cover types are similar, spatial patterns are essential for studies of the ecological functions of a landscape system. In this study, we used classical landscape indices that quantifies spatial patterns to analyze the spatial pattern consistency among different land cover datasets, and chose three datasets (GlobeLand30-2010, FROM-GLC2010, and SERVIR MEKONG2010) in northern Laos as a case study. We also analyzed spatial pattern consistency at different scales after comparing the landscape indices method with the confusion matrix method. We found that the degree of consistency between GlobeLand30-2010 and SERVIR MEKONG2010 was higher than that of GlobeLand30-2010 and FROM-GLC2010, FROM-GLC2010, and SERVIR MEKONG2010 based on the confusion matrix, mainly because of the best forest consistency and then water. However, the spatial consistency results of the landscape indices analysis show that the three datasets have large differences in the number of patches (NP), patch density (PD), and landscape shape index (LSI) at the original scale of 30 m, and decrease with the increase of the scale. Meanwhile, the aggregation index (AI) shows different changes, such as the changing trend of the forest aggregation index increasing with the scale. Our results suggested that, when using or producing land cover datasets, it is necessary not only to ensure the consistency of landscape types and areas, but also to ensure that differences among spatial patterns are minimized, especially those exacerbated by scale. Attention to these factors will avoid larger deviations and even erroneous conclusions from these data products.

Assessing the effects of ecological engineering on carbon storage by linking the CA-Markov and InVEST models

Ecological engineering has become an essential tool in efforts to address environmental crises, improve human well-being, and achieve sustainability. However, efficient assessment of changes resulting from ecological engineering remains a challenge. In this study, we evaluated the effects of ecological engineering on carbon storage in the upper reaches of the Heihe River Basin in semi-arid northwestern China by linking the CA-Markov and InVEST models. Firstly, the CA-Markov model was used to simulate land use/cover change (LUCC) following the implementation of ecological engineering programs. Then, the InVEST model was adopted to assess changes in carbon storage due to LUCC. The results showed that ecological engineering could increase carbon storage by 10.27 Tg from 2015 to 2029 by increasing the proportion of land cover types with higher carbon storage capacity. The relative error of the linked model was 0.22%, indicating that the linked model was highly applicable in assessments of the effects of ecological engineering on carbon storage in the study area. This study will provide a reference for guiding ecological engineering efforts.

A practical sampling method for assessing accuracy of detected land cover/land use change: Theoretical analysis and simulation experiments

Accuracy assessment plays a crucial role in the implementation of change detection, which is commonly used to track land surface changes and ecosystem dynamics. There are currently two major indicators for accuracy assessment of change detection: the binary change accuracy (ca) and the overall transition accuracy (ta). The overall transition accuracy has been recommended over change accuracy, because the binary change accuracy does not consider the accuracy of the types of changes of the underlying land cover classes. However, the application of overall transition accuracy has been limited by the challenge of collecting enough representative samples with a practical sampling strategy to meet the users’ requirement of precision. This study provides an iterative sampling framework to ensure that the precision of the estimated overall transition accuracy meets the users’ predefined requirement. We use a set of simulated change maps to comprehensively examine the effectiveness and robustness of the proposed sampling strategy. The simulation-based results demonstrate that the proposed framework can achieve satisfactory performance for transition accuracy assessment and it is robust against different properties of classification results and target landscapes, including the degree of fragmentation, proportions of land cover types, and temporal correlation of the classification error between individual dates. The effectiveness, robustness and practicality of the proposed sampling strategy will enable producers and users of land cover/land use change maps to get reliable and meaningful accuracy assessment for further applications.

The managed clearing: An overlooked land-cover type in urbanizing regions?

Urban ecosystem assessments increasingly rely on widely available map products, such as the U.S. Geological Service (USGS) National Land Cover Database (NLCD), and datasets that use generic classification schemes to detect and model large-scale impacts of land-cover change. However, utilizing existing map products or schemes without identifying relevant urban class types such as semi-natural, yet managed land areas that account for differences in ecological functions due to their pervious surfaces may severely constrain assessments. To address this gap, we introduce the managed clearings land-cover type–semi-natural, vegetated land surfaces with varying degrees of management practices–for urbanizing landscapes. We explore the extent to which managed clearings are common and spatially distributed in three rapidly urbanizing areas of the Charlanta megaregion, USA. We visually interpreted and mapped fine-scale land cover with special attention to managed clearings using 2012 U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) images within 150 randomly selected 1-km2 blocks in the cities of Atlanta, Charlotte, and Raleigh, and compared our maps with National Land Cover Database (NLCD) data. We estimated the abundance of managed clearings relative to other land use and land cover types, and the proportion of land-cover types in the NLCD that are similar to managed clearings. Our study reveals that managed clearings are the most common land cover type in these cities, covering 28% of the total sampled land area– 6.2% higher than the total area of impervious surfaces. Managed clearings, when combined with forest cover, constitutes 69% of pervious surfaces in the sampled region. We observed variability in area estimates of managed clearings between the NAIP-derived and NLCD data. This suggests using high-resolution remote sensing imagery (e.g., NAIP) instead of modifying NLCD data for improved representation of spatial heterogeneity and mapping of managed clearings in urbanizing landscapes. Our findings also demonstrate the need to more carefully consider managed clearings and their critical ecological functions in landscape- to regional-scale studies of urbanizing ecosystems.

Delineating and mapping riparian areas for ecosystem service assessment

AbstractRiparian buffers, the interface between terrestrial and freshwater ecosystems, have the potential to protect water bodies from land‐based pollution, and also for enhancing the delivery of a range of ecosystem services. The UK currently has no defined optimal width or maximum extent of riparian buffers for specific ecosystem services. Here, we present the first study, which attempts to (a) compare and critique different riparian buffer delineation methods and (b) investigate how ecological processes, for example, pollutant removal, nutrient cycling, and water temperature regulation, are affected spatially by proximity to the river and also within a riparian buffer zone. Our results have led to the development of new concepts for riparian delineation based on ecosystem service‐specific scenarios. Results from our study suggest that choice of delineation method will influence not only the total area of potential riparian buffers but also the proportion of land cover types included, which in turn will determine their main ecosystem provision. Thus, for some ecological processes (e.g., pollutant removal), a fixed‐distance approach will preserve and protect its ecosystem function, whereas for processes such as denitrification, a variable‐width buffer will reflect better riparian spatial variability maximizing its ecological value. In summary, riparian delineation within UK habitats should be specific to the particular ecosystem service(s) of interest (e.g., uptake of nutrients and shading), and the effectiveness of the buffer should be ground‐truthed to ensure the greatest level of protection.

Relationship between land surface temperature and land cover types based on GWR model: A case of Beijing-Tianjin-Tangshan urban agglomeration, China.

We used land cover data derived from Landsat thematic mapper (TM) and land surface temperature (LST) data from moderate-resolution imaging spectro-radiometer (MODIS) satellite images to study the variations in LST in July of different land cover types in Beijing-Tianjin-Tangshan urban agglomeration. Ordinary linear regressions (OLS) models and geographically weighted regressions (GWR) models were used to investigate the relationships between the proportions of land cover types and LST. The results showed that great variations in LST occurred among different land cover types. The average LST ranged from high to low in the order of developed land (40.92±3.49 ℃), cultivated land (39.74±3.74 ℃), wetland (35.42±4.33 ℃), and forested land (34.43±4.16 ℃). The proportions of land cover types were significantly related to LST, but with spatial non-stationarity. This might be due to inherent difference in land cover across locations, and the surrounding environments. GWR models had higher R2 values, compared to OLS, indicating better model performance. In addition, GWR models could reveal the spatial non-stationarity of the relations between LST and the proportions of different land cover types.

Floristic diversity of meadow steppes in the Western Siberian Plain: effects of abiotic site conditions, management and landscape structure

Temperate grasslands have suffered from severe habitat loss and degradation worldwide. In Russia, vast areas of forest-steppe grasslands have been converted to cropland during Soviet times, whilst remaining grasslands were often intensively grazed. Contrastingly, the collapse of the Soviet Union have resulted in a massive reduction in livestock numbers and cessation of management. Albeit relatively large natural grassland areas remained in the Western Siberian Plain, their present condition is poorly studied. We analysed plant species composition, functional structure and richness of grassland communities and tested for the effect of local factors (management, abiotic site conditions) and landscape factors (patch size, proportion of land cover types) on diversity patterns. Abiotic site conditions, mainly soil moisture and salinity, differentiated distinct community types. Overall, species richness was highest in meadow steppe communities with lower soil moisture and salinity. Grazing intensity and litter accumulation due to cessation of management were significant negative related to species richness and shaped the functional structure. At the landscape scale, diversity in meadow steppe grasslands was higher in forest-grassland mosaics and in small remnants isolated in a matrix of cropland. Our findings highlight that meadow steppes suffered massively under the historical habitat loss and high grazing pressure. Small species-rich remnants are evidence of the former extent of meadow steppe habitats in agricultural landscape, but are likely threatened by an extinction debt. Low intense, irregular mowing maintained species-rich meadow steppe in forest- grassland mosaics, but currently such practices are declining.

A SPLIT Model for Extraction of Subpixel Impervious Surface Information

This paper introduces a Subpixel Proportional Land cover Information Transformation (SPLIT) model to extract proportions of impervious surfaces in urban and suburban areas. High spatial resolution airborne Digital Multispectral Videography (DMSV) data provided subpixel information for Landsat TM data. The SPLIT model employed a Modularized Artificial Neural Network (MANN) to integrate multi-sensor remote sensing data and to extract proportions of impervious surfaces and other types of land cover within TM pixels. Through a control unit, the MANN was able to decompose a complex task into multiple subtasks by using a group of sub-networks. The SPLIT model identified spectral relations between TM pixel values and the corresponding DMSV subpixel patterns. The established relationship allows extrapolation of the SPLIT model to the areas beyond DMSV data coverage. We applied five intervals, i.e., 81 percent, to map the subpixel proportions of land cover types. We extrapolated the SPLIT model from training sites that have both TM and DMSV coverage into the entire DuPage County with TM data as the input. The extrapolation received 82.9 percent overall accuracy for the extracted proportions of urban impervious surface.

Problems in upscaling of high resolution remote sensing data to coarse spatial resolution over land surface

Characterization of land cover type for a grid cell (50 to 100 km) of General Circulation Models has to be achieved through spatial integration of satellite data available at higher spatial resolution. Preservation of information integrity is required during such upscaling and a suitable algorithm is to be developed and validated. The 36.25 and 72.5 m resolution IRS Linear Imaging Self Scanner (LISS) data were used for studying (i) change in proportion of the area under given land cover classes with the degradation in resolution and (ii) correlation between upscaled 72.5 m resolution (from 36.25 m) and observations in 72.5 m resolutions, and further upscaled resolutions, for different land cover types using different upscaling algorithms. In general, the percentage proportion of land cover types decreased with degradation of spatial resolution and the fractal method gave best correlations for water and agricutlure classes.