Evaluating spatial resolution enhancement on impervious surface detection using support vector machine

Impervious surface area (ISA) is considered as an indicator of environment change and is regarded as an important input parameter for hydrological cycle simulation, water management and area pollution assessment. The Pearl River Delta (PRD), the 3rd most important economic district of China, is chosen in this paper to extract the ISA information based on Landsat images of 1998, 2003 and 2008 by using a linear spectral un-mixing method and to monitor impervious surface change by analyzing the multi-temporal Landsat-derived fractional impervious surface. Results of this study were as follows: (1) the area of ISA in the PRD increased 79.09% from 1998 to 2003 and 26.88% from 2003 to 2008 separately; (2) the spatial distribution of ISA was described according to the 1998/2003 percentage respectively. Most of middle and high percentage ISA was located in northwestern and southeastern of the whole delta, and middle percentage ISA was mainly located in the city interior, high percentage ISA was mainly located in the suburban around the city accordingly; (3) the expanding direction and trend of high percentage ISA was discussed in order to understand the change of urban in this delta; High percentage ISA moved from inner city to edge of urban area during 1998–2003 and moved to the suburban area that far from the urban area mixed with jumpily and gradually during 2003–2008. According to the discussion of high percentage ISA spatial expanded direction, it could be found out that high percentage ISA moved outward from the centre line of Pearl River of the whole delta while a high ISA percentage in both shores of the Pearl River Estuary moved toward the Pearl River; (4) combining the change of ISA with social conditions, the driving relationship was analyzed in detail. It was evident that ISA percentage change had a deep relationship with the economic development of this region in the past ten years. Contemporaneous major sport events (16th Asia Games of Guangzhou, 26th Summer Universidad of Shenzhen) and the government policies also promoted the development of the ISA. Meanwhile, topographical features like the National Nature Reserve of China restricted and affected the expansion of the ISA. Above all, this paper attempted to extract ISA in a major region of the PRD; the temporal and spatial analyses to PRD ISA demonstrated the drastic changes in developed areas of China. These results were important and valuable for land use management, ecological protection and policy establishment.

Estimating the distribution of impervious surfaces and vegetation is important for analysing urban landscapes and their thermal environment. The application of a crisp classification of land-cover types to analyse urban landscape patterns and land surface temperature (LST) in detail presents a challenge, mainly due to the complex characteristics of urban landscapes. In this article, sub-pixel percentage impervious surface areas (ISAs) and fractional vegetation cover (FVC) were extracted from bitemporal Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) data by linear spectral mixture analysis (LSMA). Their accuracy was assessed with proportional area estimates of the impervious surface and vegetation extracted from high-resolution data. A range approach was used to classify percentage ISA into different categories by setting thresholds of fractional values and these were compared for their LST patterns. For each ISA category, FVC, LST, and percentage ISA were used to quantify the urban thermal characteristics of different developed areas in the city of Fuzhou, China. Urban LST scenarios in different seasons and ISA categories were simulated to analyse the seasonal variations and the impact of urban landscape pattern changes on the thermal environment. The results show that FVC and LST based on percentage ISA can be used to quantitatively analyse the process of urban expansion and its impacts on the spatial–temporal distribution patterns of the urban thermal environment. This analysis can support urban planning by providing knowledge on the climate adaptation potential of specific urban spatial patterns.

The growing intensity of impervious surface area (ISA) is one of the most striking effects of urban growth. The expansion of ISA gives rise to a set of changes on the physical environment, impacting the quality of life of the human population as well as the dynamics of fauna and flora. Hence, due to its importance, the present study aimed to examine the ISA distribution in the Metropolitan Region of São Paulo (MRSP), Brazil, using satellite imagery from the Landsat-8 Operational Land Imager (OLI) instrument. In contrast to other investigations that primarily focus on the accuracy of the estimate, the proposal of this study is—besides generating a robust estimate—to perform an integrated analysis of the impervious-surface distribution at pixel scale with the variability present in different territorial units, namely municipalities, sub-prefecture and districts. The importance of this study is that it strengthens the use of information related to impervious cover in the territorial planning, providing elements for a better understanding and connection with other spatial attributes. Reducing the dimensionality of the dataset (visible, near-infrared and short-wave infrared bands) by Karhune–Loeve analysis, the first three principal components (PCs) contained more than 99% of the information present in the original bands. Projecting PC1, PC2 and PC3 onto a series of two-dimensional (2D) scatterplots, four endmembers—Low Albedo (Dark), High Albedo (Substrate), Green Vegetation (GV) and Non-Photosynthetic Vegetation (NPV)—were visually selected to produce the unmixing estimates. The selected endmembers fitted the model well, as the propagated error was consistently low (root-mean-square error = 0.005) and the fraction estimates at pixel scale were found to be in accordance with the physical structures of the landscape. The impervious surface fraction (ISF) was calculated by adding the Dark and Substrate fraction imagery. Reconciling the ISF with reference samples revealed the estimates to be reliable (R2 = 0.97), regardless of an underestimation error (~8% on average) having been found, mostly over areas with higher imperviousness rates. Intra-pixel variability was combined with the territorial units of analysis through a modification of the Lorenz curve, which permitted a straightforward comparison of ISF values at different reference scales. Good adherence was observed when the original 30-m ISF was compared to a resampled 300-m ISF, but with some differences, suggesting a systematic behavior with the degradation of pixel resolution tending to underestimate lower fractions and overestimate higher ones; furthermore, discrepancies were bridged with the increase of scale analysis. The analysis of the IFS model also revealed that, in the context of the MRSP, gross domestic product (GDP) has little potential for explaining the distribution of impervious areas on the municipality scale. Finally, the ISF model was found to be more sensitive in describing impervious surface response than other well-known indices, such as Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI).

Urban heat island (UHI) attenuation is an essential aspect for maintaining environmental sustainability at a local, regional, and global scale. Although impervious surfaces (IS) and green spaces have been confirmed to have a dominant effect on the spatial differentiation of the urban land surface temperature (LST), comprehensive temporal and quantitative analysis of their combined effects on LST and surface urban heat island intensity (SUHII) changes is still partly lacking. This study took the plain area of Beijing, China as an example. Here, rapid urbanization and a large-scale afforestation project have caused distinct IS and vegetation cover changes within a small range of years. Based on 8 scenes of Landsat 5 TM/7ETM/8OLI images (30 m × 30 m spatial resolution), 920 scenes of EOS-Aqua-MODIS LST images (1 km × 1 km spatial resolution), and other data/information collected by different approaches, this study characterized the interrelationship of the impervious surface area (ISA) dynamic, forest cover increase, and LST and SUHII changes in Beijing’s plain area during 2009–2018. An innovative controlled regression analysis and scenario prediction method was used to identify the contribution of ISA change and afforestation to SUHII changes. The results showed that percent ISA and forest cover increased by 6.6 and 10.0, respectively, during 2009–2018. SUHIIs had significant rising tendencies during the decade, according to the time division of warm season days (summer days included) and cold season nights (winter nights included). LST changes during warm season days responded positively to a regionalized ISA increase and negatively to a regionalized forest cover increase. However, during cold season nights, LST changes responded negatively to a slight regionalized ISA increase, but positively to an extensive regionalized ISA increase, and LST variations responded negatively to a regionalized forest cover increase. The effect of vegetation cooling was weaker than ISA warming on warm season days, but the effect of vegetation cooling was similar to that of ISA during cold season nights. When it was assumed that LST variations were only caused by the combined effects of ISA changes and the planting project, it was found that 82.9% of the SUHII rise on warm season days (and 73.6% on summer days) was induced by the planting project, while 80.6% of the SUHII increase during cold season nights (and 78.9% during winter nights) was caused by ISA change. The study presents novel insights on UHI alleviation concerning IS and green space planning, e.g., the importance of the joint planning of IS and green spaces, season-oriented UHI mitigation, and considering the thresholds of regional IS expansion in relation to LST changes.

Among the global Earth system changes, human-induced land-cover and land-use changes (LULCC) play significant roles in sustainability of ecosystems. Suburban sprawl, for example, is one of the major components of LULCC that develops urban impervious surface area (ISA) across the landscapes. Increasing ISA is a major environmental issue that has profound impacts on hydrology and climate. Coastal state of Rhode Island has experienced problems associated with urban runoffs due to the alteration of ISA on the landscape. Precise and accurate coverage and location of ISA are key parameters in ISA related environmental studies. Due to the limitations of existing coarse spatial resolution ISA data and current methods for extraction of ISA from high spatial resolution remote sensing imageries, this study developed an algorithm of multiple agent segmentation and classification (MASC) to extract ISA information from high spatial resolution remote sensing imageries. The MASC model includes submodels of segmentation, shadow-effect, MANOV A-based classification, and post-classification. Based on the MASC model, this study built the 1-meter high spatial resolution ISA dataset for the state of Rhode Island, and revealed its spatial patterns. The result indicates that, as of 2004, 10% of the state land has been covered by ISA. The major population centers and historical cities, such as the Providence, Woonsocket, and Newport, have ISA over 30%. The heavily settled suburban communities have ISA between 10% and 30%. Only 17 out of 39 towns in the state have less than 10% ISA. The average ISA for the coastal towns is 14%. Because most stream quality indicators are predicted to decline when watershed ISA exceeds 10%, the results from this study serve as an alarming indicator for managing the state's watershed and coastal ecosystems. It is important to develop scientific basis for observing and modeling watershed hydrologic dynamic with emphasis on how the hydrologic processes are affected by the spatial heterogeneity of ISA, and to improve the understanding of influence of ISA on hydrologic cycle in watersheds. This developed a distributed object-oriented rainfall-runoff simulation (DORS) model that enhances capability and performance of hydrologic modeling with incorporation of high spatial resolution ISA information. With the innovative process of object-oriented spatial units, the DORS model can reduce data volume, increase computational efficiency, strengthen representation of watersheds and utilize the data in variable scales. The DORS model provides a framework to integrate remote sensing data and the derived products in different scale for the simulation of

Implying the prosperity and development of the city, impervious surface area (ISA) is playing an increasingly important role in ecological processes, microclimate, material and energy flows, and urban flood. The free sub-meter resolution Google Earth image, which is integrated by several high spatial resolution data, appears to have potential for high-resolution ISA extraction, where present study is rare and performances remain to be improved. Due to the high spatial and spectral variation of the urban environment as well as confusion between ISA and soil, the accurate delineating of ISA with traditional (direct) methods can be costly and time-consuming, which is in a word resource-intensive. However, this paper presents a novel indirect ISA extraction conceptual model and a new detecting and masking background land cover (DMBLC) approach that: uses a freely available, high-resolution dataset; requires a reduced set of training samples; and consists of relatively simple, common, and feasible image processing steps. The key characteristic of DMBLC is to detect the background of ISA (vegetation, soil, and water) accurately and obtain the ISA by masking the background. The approach relies on background detection to avoid the predicaments of direct ISA extraction. Water can be directly gained by water body vector data, in DMBLC; mixture tuned matched filtering (MTMF) is exploited to detect vegetation and soil, image segmentation is used to mitigate the spectral variation problem within the same land cover, and segment rectangularity reduces the confusion between ISA and soil. From experiments in a core area of Fuzhou, China, the DMBLC approach reached high performance and outperformed the powerful traditional support vector machines (SVM) method (overall accuracy of 94.45% and Kappa coefficient of 0.8885, compared to 86.44% and 0.7329, respectively). From the comparison of different levels of complexity within the inner processing steps, it is confirmed that the DMBLC approach is a powerful and flexible changed framework for indirect ISA extraction, which can be improved by using more advanced inner methods.

Influence of spatiotemporal changes of impervious surface on the urban thermal environment: A case of Huai'an central urban area

Here we used remote sensing data from multiple sources (time-series of Landsat and Sentinel images) to map the impervious surface area (ISA) at five-year intervals from 1990 to 2015, and then converted the results into a standardized dataset of the built-up area for 433 Chinese cities with 300,000 inhabitants or more, which were listed in the United Nations (UN) World Urbanization Prospects (WUP) database (including Mainland China, Hong Kong, Macao and Taiwan). We employed a range of spectral indices to generate the 1990–2015 ISA maps in urban areas based on remotely sensed data acquired from multiple sources. In this process, various types of auxiliary data were used to create the desired products for urban areas through manual segmentation of peri-urban and rural areas together with reference to several freely available products of urban extent derived from ISA data using automated urban–rural segmentation methods. After that, following the well-established rules adopted by the UN, we carried out the conversion to the standardized built-up area products from the 1990–2015 ISA maps in urban areas, which conformed to the definition of urban agglomeration area (UAA). Finally, we implemented data postprocessing to guarantee the spatial accuracy and temporal consistency of the final product.The standardized urban built-up area dataset (SUBAD–China) introduced here is the first product using the same definition of UAA adopted by the WUP database for 433 county and higher-level cities in China. The comparisons made with contemporary data produced by the National Bureau of Statistics of China, the World Bank and UN-habitat indicate that our results have a high spatial accuracy and good temporal consistency and thus can be used to characterize the process of urban expansion in China.The SUBAD–China contains 2,598 vector files in shapefile format containing data for all China's cities listed in the WUP database that have different urban sizes and income levels with populations over 300,000. Attached with it, we also provided the distribution of validation points for the 1990–2010 ISA products of these 433 Chinese cities in shapefile format and the confusion matrices between classified data and reference data during different time periods as a Microsoft Excel Open XML Spreadsheet (XLSX) file.Furthermore, The standardized built-up area products for such cities will be consistently updated and refined to ensure the quality of their spatiotemporal coverage and accuracy. The production of this dataset together with the usage of population counts derived from the WUP database will close some of the data gaps in the calculation of SDG11.3.1 and benefit other downstream applications relevant to a combined analysis of the spatial and socio-economic domains in urban areas.

Evaluation of Luojia 1-01 nighttime light imagery for impervious surface detection: A comparison with NPP-VIIRS nighttime light data

Timely and rapidly mapping impervious surface area (ISA) and monitoring its spatial-temporal change pattern can deepen our understanding of the urban process. However, the complex spectral variability and spatial heterogeneity of ISA caused by the increased spatial resolution poses a great challenge to accurate ISA dynamics monitoring. This research selected Jinan City as a case study to boost ISA mapping performance through integrating the dual-attention CBAM module, SE module and focal loss function into the Deeplabv3+ model using Sentinel-2 data, and subsequently examining ISA spatial-temporal evolution using the generated annual time-series ISA data from 2017 to 2021. The experimental results demonstrated that (a) the improved Deeplabv3+ model achieved satisfactory accuracy in ISA mapping, with Precision, Recall, IoU and F1 values reaching 82.24%, 92.38%, 77.01% and 0.87, respectively. (b) In a comparison with traditional classification methods and other state-of-the-art deep learning semantic segmentation models, the proposed method performed well, qualitatively and quantitatively. (c) The time-series analysis on ISA distribution revealed that the ISA expansion in Jinan City had significant directionality from northeast to southwest from 2017 to 2021, with the number of patches as well as the degree of connectivity and aggregation increasing while the degree of fragmentation and the complexity of shape decreased. Overall, the proposed method shows great potential in generating reliable times-series ISA data and can be better served for fine urban research.

The expansion of impervious surface area (ISA) in megacities of China often leads to land surface temperature (LST) aggregation effects, which affect living environments by impacting thermal comfort levels, thus becoming an issue of public concern. However, from an urban–rural synchronous comparison perspective, the study of LST responses to ISA changes is still lacking in the central coastal megalopolises of China. To solve this issue, a collaborative methodology of artificial digitization—fully constrained least squares mixed pixel decomposition—split-window algorithm—PCACA model was established for Qingdao using land use dataset and remote sensing images. The conclusions are below. Long time series of land use monitoring indicated that the expansion ratios of urban and rural areas were 131.29% and 43.42% in the past 50 years (i.e., from 1970 to 2020). Within urban and rural areas, a synchronous ISA increase was observed, with ratios of +9.14% (140.55 km2) and +7.94% (28.04 km2), respectively. Higher ratios and area changes were found in the urban regions, and a similar ISA change pattern in both urban and rural regions was captured by the ISA horizontal epitaxial expansion and vertical density enhancement. Further, the horizontal gradient effect displayed that the mean LSTs were 28.75 °C, 29.77 °C and 31.91 °C in the urban areas and 28.73 °C, 29.66 °C and 31.65 °C in the rural areas in low-, medium-, and high-density ISAs. The vertical density effect showed that the LST change was 1.02 °C and 2.14 °C in the urban areas but 0.93 °C and 1.99 °C in the rural areas during the ISA-density transition from low- to medium- and from medium- to high-density, respectively. Potential surface thermal indicators were assessed, and the urban regions displayed higher sensible heat flux (280.13 W/m2) compared to the rural regions (i.e., 274.76 W/m2). The mechanism effect of the ISA changes on LST in the urban and rural regions was revealed. These findings form a new comparative perspective of the urban–rural synchronous change in the central coastal megalopolis of China and can provide a practical reference for relevant studies.

It is necessary to understand the relationship between the impervious surface area (ISA) distribution, variation trends and potential driving forces over Dongying, Shandong Province. We extracted ISA information from Landsat images with 3–5 year intervals during 1995 to 2018 using Minimum Noise Fraction (MNF) transform, Pixel Purity Index (PPI), and Linear Spectral Mixture Analysis (LSMA), followed by the analysis on three driving forces of ISA expansion (physical geography, socioeconomic factors, and urban cultural features). Our results show the retrieved ISA thematic map fit the limited requirement of root mean square error (RMSE). The correct classification accuracy of ISA is greater than 83.08%. Further, the cross–comparison exhibits the general consistent with the ISA distribution of the land use classification map published by the National Basic Geographic Information Center. The gradual increasing trend can be captured on the expansion of ISA from 1995 to 2018. Despite of the central region always shown as the high ISA density, it still keeps increasing annually and radiating the surrounding region, especially in the southward which has formed into a new large–scale and high intensity of ISA in 2015–2018. Though the ISA patches scattered in the west region or along the northern and eastern part of the ocean coastline are still small, the expansion trend of ISA can be detected. The expansion intensity index (EII) of ISA measuring the situation of its expansion changes from the lowest value 0.12% between 1995 and 2000 up to the highest 0.73% between 2000 and 2005. Richly endowed by nature, the city’s natural geographical environment provides an elevated chance of further urbanization. The rapid increase of regional economy provides a fundamental driving force for expanding ISAs. The development of urban culture promotes the sustainable development of ISAs. Our results provide a scientific basis for future urban land use management, construction planning, and environmental protection in Dongying.

Different urban growth patterns have various impact degrees on the urban ecosystem and environment. Impervious surface, a typical artificial construction can be used to reflect urban development. Therefore, this study estimated the spatiotemporal dynamics and expansion patterns of impervious surface area (ISA) in the Guangdong-Hong Kong-Macau (GHM) Bay Area since the establishment of the “Pearl River Delta economic zone” in 1994. Landsat time-series images were used to map the distribution of the ISA based on the combinational biophysical composition index (CBCI) and the bidirectional temporal filtering method (BTFM). The results indicated that the ISA in the GHM Bay Area drastically expanded from 569.23 km2 in 1994 to 10,200.53 km2 in 2016. In addition, the aggregation index (AI) value of the high-density area showed a decreasing trend from 1994 to 2004. However, the value of each landscape metric rapidly increased after 2004. Moreover, the mean ratio of the major axis to the minor axis of standard deviational ellipses from 1994 to 2004 was higher than that from 2005 to 2016. The results of landscape metrics and standard deviational ellipses indicated that the ISA growth pattern changed from edge expanding and leapfrogging to infilling and consolidation, with a turning point in 2004. Moreover, the principal sprawl orientation of the ISA was northwest to southeast before 2004. After 2004, the expansion direction of the ISA was less obvious due to the development pattern of infilling and consolidation. The rapid increase of GDP and population are the driving forces of urban expansion. However, topography and ecological protection policies as the limiting factors, which caused the infilling of the inner city and redevelopment of old urban areas.

An easily implemented method to estimate impervious surface area on a large scale from MODIS time-series and improved DMSP-OLS nighttime light data

The spatiotemporal evolution of an impervious surface (IS) is significant for urban planning. In this paper, the IS was extracted and its spatiotemporal evolution for the Chengdu urban area was analyzed based on Landsat imagery. Our experimental results indicated that convolutional neural networks achieved the better performance with an overall accuracy of 98.32%, Kappa coefficient of 0.98, and Macro F1 of 98.28%, and the farmland was replaced by IS from 2001 to 2017, and the IS area (ISA) increased by 51.24 km2; that is, the growth rate was up to 13.8% in sixteen years. According to the landscape metrics, the IS expanded and agglomerated into large patches from small fragmented ones. In addition, the gross domestic product change of the secondary industry was similar to the change of ISA between 2001 and 2017. Thus, the spatiotemporal evolution of IS was associated with the economic development of the Chengdu urban area in the past sixteen years.