scholarly journals A Novel Query Strategy-Based Rank Batch-Mode Active Learning Method for High-Resolution Remote Sensing Image Classification

2021 ◽  
Vol 13 (11) ◽  
pp. 2234
Author(s):  
Xin Luo ◽  
Huaqiang Du ◽  
Guomo Zhou ◽  
Xuejian Li ◽  
Fangjie Mao ◽  
...  
Keyword(s):  
Land Use ◽  
Active Learning ◽  
Euclidean Distance ◽  
Urban Land Use ◽  
Misclassification Rate ◽  
Training Set ◽  
Batch Mode ◽  
Land Use Types ◽  
Information Divergence ◽  
Uncertainty Score

An informative training set is necessary for ensuring the robust performance of the classification of very-high-resolution remote sensing (VHRRS) images, but labeling work is often difficult, expensive, and time-consuming. This makes active learning (AL) an important part of an image analysis framework. AL aims to efficiently build a representative and efficient library of training samples that are most informative for the underlying classification task, thereby minimizing the cost of obtaining labeled data. Based on ranked batch-mode active learning (RBMAL), this paper proposes a novel combined query strategy of spectral information divergence lowest confidence uncertainty sampling (SIDLC), called RBSIDLC. The base classifier of random forest (RF) is initialized by using a small initial training set, and each unlabeled sample is analyzed to obtain the classification uncertainty score. A spectral information divergence (SID) function is then used to calculate the similarity score, and according to the final score, the unlabeled samples are ranked in descending lists. The most “valuable” samples are selected according to ranked lists and then labeled by the analyst/expert (also called the oracle). Finally, these samples are added to the training set, and the RF is retrained for the next iteration. The whole procedure is iteratively implemented until a stopping criterion is met. The results indicate that RBSIDLC achieves high-precision extraction of urban land use information based on VHRRS; the accuracy of extraction for each land-use type is greater than 90%, and the overall accuracy (OA) is greater than 96%. After the SID replaces the Euclidean distance in the RBMAL algorithm, the RBSIDLC method greatly reduces the misclassification rate among different land types. Therefore, the similarity function based on SID performs better than that based on the Euclidean distance. In addition, the OA of RF classification is greater than 90%, suggesting that it is feasible to use RF to estimate the uncertainty score. Compared with the three single query strategies of other AL methods, sample labeling with the SIDLC combined query strategy yields a lower cost and higher quality, thus effectively reducing the misclassification rate of different land use types. For example, compared with the Batch_Based_Entropy (BBE) algorithm, RBSIDLC improves the precision of barren land extraction by 37% and that of vegetation by 14%. The 25 characteristics of different land use types screened by RF cross-validation (RFCV) combined with the permutation method exhibit an excellent separation degree, and the results provide the basis for VHRRS information extraction in urban land use settings based on RBSIDLC.

THE IMPACT OF DIFFERENT URBAN LAND USE TYPES ON AIR POLLUTION IN THE MEGACITY OF SÃO PAULO

2020 ◽  
Vol 7 (1) ◽  
pp. 91
Author(s):  
Júlio Barboza Chiquetto ◽  
Maria Elisa Siqueira Silva ◽  
Rita Yuri Ynoue ◽  
Flávia Noronha Dutra Ribieiro ◽  
Débora Souza Alvim ◽  
...  
Keyword(s):  
Land Use ◽  
Air Pollution ◽  
Urban Land ◽  
Sao Paulo ◽  
Urban Land Use ◽  
São Paulo ◽  
Land Use Types ◽  
The Impact

A poluição do ar é influenciada por fatores naturais e antropogênicos. Quatro pontos de monitoramento (veicular, comercial, residencial e background urbano (BGU))da poluição do ar em São Paulo foram avaliados durante 16 anos, revelando diferenças significativas devidoao uso do solo em todas as escalas temporais. Na escala diurna, as concentrações de poluentes primários são duas vezes mais altas nos pontos veicular e residencial do que no ponto BGU, onde a concentração de ozonio (O3) é 50% mais alta. Na escala sazonal, as concentrações de monóxido de carbono(CO) variaram em 80% devido ao uso do solo, e 55% pela sazonalidade.As variações sazonais ede uso do solo exercem impactos similares nas concentrações de O3 e monóxido de nitrogênio (NO). Para o material particulado grosso (MP10) e o dióxido de nitrogênio(NO2), as variações sazonais são mais intensas do que as por uso do solo. Na série temporal de 16 anos, o ponto BGU apresentou correlações mais fortes e significativas entre a média mensal de ondas longas (ROL) e o O3 (0,48) e o MP10 (0,37), comparadas ao ponto veicular (0,33 e 0,22, respectivamente). Estes resultados confirmam que o uso do solo urbano tem um papel significativo na concentração de poluentes em todas as escalas de análise, embora a sua influência se torne menos pronunciada em escalas maiores, conforme a qualidade do ar transita de um sistema antropogênico para um sistema natural. Isto poderá auxiliar decisões sobre políticas públicas em megacidades envolvendo a modificação do uso do solo.

scholarly journals Micropollutants in Urban Stormwater Runoff of Different Land Uses

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1312
Author(s):  
Daniel Wicke ◽  
Andreas Matzinger ◽  
Hauke Sonnenberg ◽  
Nicolas Caradot ◽  
Rabea-Luisa Schubert ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Land Use ◽  
Surface Waters ◽  
Flame Retardants ◽  
Stormwater Runoff ◽  
Monitoring Program ◽  
Quality Standards ◽  
Urban Land Use ◽  
Organic Micropollutants ◽  
Land Use Types

The main aim of this study was a survey of micropollutants in stormwater runoff of Berlin (Germany) and its dependence on land-use types. In a one-year monitoring program, event mean concentrations were measured for a set of 106 parameters, including 85 organic micropollutants (e.g., flame retardants, phthalates, pesticides/biocides, polycyclic aromatic hydrocarbons (PAH)), heavy metals and standard parameters. Monitoring points were selected in five catchments of different urban land-use types, and at one urban river. We detected 77 of the 106 parameters at least once in stormwater runoff of the investigated catchment types. On average, stormwater runoff contained a mix of 24 µg L−1 organic micropollutants and 1.3 mg L−1 heavy metals. For organic micropollutants, concentrations were highest in all catchments for the plasticizer diisodecyl phthalate. Concentrations of all but five parameters showed significant differences among the five land-use types. While major roads were the dominant source of traffic-related substances such as PAH, each of the other land-use types showed the highest concentrations for some substances (e.g., flame retardants in commercial area, pesticides in catchment dominated by one family homes). Comparison with environmental quality standards (EQS) for surface waters shows that 13 micropollutants in stormwater runoff and 8 micropollutants in the receiving river exceeded German quality standards for receiving surface waters during storm events, highlighting the relevance of stormwater inputs for urban surface waters.

Urban land use types contribute to grassland conservation: The example of Berlin

2013 ◽  
Vol 12 (3) ◽  
pp. 263-272 ◽  
Author(s):  
Leonie K. Fischer ◽  
Moritz von der Lippe ◽  
Ingo Kowarik
Keyword(s):  
Land Use ◽  
Urban Land ◽  
Urban Land Use ◽  
Grassland Conservation ◽  
Land Use Types

scholarly journals Inferring Urban Land Use from Multi-Source Urban Mobility Data Using Latent Multi-View Subspace Clustering

2021 ◽  
Vol 10 (5) ◽  
pp. 274
Author(s):  
Qiliang Liu ◽  
Weihua Huan ◽  
Min Deng ◽  
Xiaolin Zheng ◽  
Haotao Yuan
Keyword(s):  
Land Use ◽  
Subspace Clustering ◽  
Urban Land ◽  
Urban Land Use ◽  
Single Type ◽  
Underlying Structure ◽  
Urban Mobility ◽  
Trajectory Data ◽  
Mobility Data ◽  
Land Use Types

In the era of big data, vast urban mobility data introduce new opportunities to infer urban land use from the perspective of social function. Most existing works only derive land use information from a single type of urban mobility dataset, which is typically biased and results in difficulty obtaining a comprehensive view of urban land use. It remains challenging to fuse high-dimensional and noisy multi-source urban mobility data to infer urban land use. This study aimed to infer urban land use from multi-source urban mobility data using latent multi-view subspace clustering. The variation in the number of origin/destination points over time was initially used to characterize land use types. Then, a latent multi-view representation was applied to construct the common underlying structure shared by multi-source urban mobility data and effectively deal with noise. Finally, based on the latent multi-view representation, the subspace clustering method was used to infer the land use types. Experiments on taxi trajectory data and bus smart card data in Beijing reveal that, compared with the method using a single type of urban mobility dataset and the weighted fusion method, the approach presented in this study obtains the highest detection rate of land use. The urban land use inferred in this study provides calibration and reference for urban planning.

scholarly journals Spatial-Temporal Analysis of Human Dynamics on Urban Land Use Patterns Using Social Media Data by Gender

2018 ◽  
Vol 7 (9) ◽  
pp. 358 ◽  
Author(s):  
Chengcheng Lei ◽  
An Zhang ◽  
Qingwen Qi ◽  
Huimin Su ◽  
Jianghao Wang
Keyword(s):  
Land Use ◽  
Urban Land Use ◽  
Moran’S I ◽  
Land Use Patterns ◽  
Moran's I ◽  
Residential Land ◽  
Human Dynamics ◽  
Use Patterns ◽  
Land Use Types ◽  
Olympic Village

The relationship between urban human dynamics and land use types has always been an important issue in the study of urban problems in China. This paper used location data from Sina Location Microblog (commonly known as Weibo) users to study the human dynamics of the spatial-temporal characteristics of gender differences in Beijing’s Olympic Village in June 2014. We applied mathematical statistics and Local Moran’s I to analyze the spatial-temporal distribution of Sina Microblog users in 100 m × 100 m grids and land use patterns. The female users outnumbered male users, and the sex ratio ( S R varied under different land use types at different times. Female users outnumbered male users regarding residential land and public green land, but male users outnumbered female users regarding workplace, especially on weekends, as the S R on weekends ( S R was 120.5) was greater than that on weekdays ( S R was 118.8). After a Local Moran’s I analysis, we found that High–High grids are primarily distributed across education and scientific research land and residential land; these grids and their surrounding grids have more female users than male users. Low–Low grids are mainly distributed across sports centers and workplaces on weekdays; these grids and their surrounding grids have fewer female users than male users. The average number of users on Saturday was the highest value and, on weekends, the number of female and male users both increased in commercial land, but male users were more active than female users ( S R was 110).

Relative importance of urban and non-urban land-use types for potential denitrification derived N2O: insights from a regional study

2018 ◽  
Vol 109 (3-4) ◽  
pp. 453-460
Author(s):  
Hui-Juan XU ◽  
Manuel DELGADO-BAQUERIZO ◽  
Fu-Xia PAN ◽  
Xin-Li AN ◽  
Brajesh K. SINGH ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Land Use ◽  
Soil Ph ◽  
Human Activities ◽  
Regional Scale ◽  
Urban Land ◽  
Urban Land Use ◽  
Relative Importance ◽  
Potential Denitrification ◽  
Land Use Types

ABSTRACTIdentifying the relative importance of urban and non-urban land-use types for potential denitrification derived N2O at a regional scale is critical for quantifying the impacts of human activities on nitrous oxide (N2O) emission under changing environments. In this study we used a regional dataset from China including 197 soil samples and six land-use types to evaluate the main predictors (land use, heavy metals, soil pH, soil moisture, substrate availability, functional and broad microbial abundances) of potential denitrification using multivariate and pathway analysis. Our results provide empirical evidence that soils on farms have the greatest potential denitrifying ability (PDA) (10.92±6.08ng N2O-N·g–1 dry soil·min–1) followed by urban soil (6.80±5.35ng N2O-N·g–1 dry soil·min–1). Our models indicate that land use (low vs. high human activity), followed by total nitrogen (TN) and heavy metals (Cu, Zn, Pb, Cd) was the most important driver of PDA. In addition, our path analysis suggests that at least part of the impacts of land use on potential denitrification were mediated via microbial abundance, soil pH and substrates including TN, dissolved organic carbon and nitrate. This study identifies the main predictors of denitrification at a regional scale which is needed to quantify the impact of human activities on ecosystem functionality under changing conditions.

scholarly journals Exploring Impact of Spatial Unit on Urban Land Use Mapping with Multisource Data

2020 ◽  
Vol 12 (21) ◽  
pp. 3597
Author(s):  
Xuanyan Dong ◽  
Yue Xu ◽  
Leping Huang ◽  
Zhigang Liu ◽  
Yi Xu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Urban Land ◽  
Urban Land Use ◽  
Remote Sensing Images ◽  
Social Sensing ◽  
Sensing Data ◽  
Object Based ◽  
Land Use Types ◽  
Functional Areas

The ability to precisely map urban land use types can significantly aid urban planning and urban system understanding. In recent years, remote sensing images and social sensing data have been frequently used for urban land use mapping. However, there still remains a problem: what is the best basic unit for fusing remote sensing images with social sensing data? The aim of this study is to explore the impact of spatial units on urban land use mapping, with remote sensing images and social sensing data of Shenzhen City, China. Three different basic units were first applied to delineate urban land use types, and for each unit, a word dictionary was built by fusing natural–physical features from high spatial resolution (HSR) remote sensing images and the socioeconomic semantic features from point of interest (POI) data. The latent Dirichlet allocation (LDA) algorithm and random forest methods were then applied to map the land use of the Futian district—the core region of Shenzhen. The experiment demonstrates that: (1) No matter what kind of spatial unit, it is beneficial to fuse multisource data to improve the performance. However, when using different spatial units, the importances of features are different. (2) Using block-based spatial units results in the final map looking the best. However, a great challenge of this approach is that the scale is too coarse to handle mixed functional areas. (3) Using grid- and object-based units, the problem of mixed functional areas can be better solved. Additionally, the object-based land use map looks better from our visual interpretation. Accordingly, the results of this study could give other researchers references and advice for future studies.

scholarly journals Simulating Intraurban Land Use Dynamics under Multiple Scenarios Based on Fuzzy Cellular Automata: A Case Study of Jinzhou District, Dalian

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Jun Yang ◽  
Weiling Liu ◽  
Yonghua Li ◽  
Xueming Li ◽  
Quansheng Ge
Keyword(s):  
Land Use ◽  
Cellular Automata ◽  
Land Use Changes ◽  
Urban Land Use ◽  
Multiple Sources ◽  
Development Mode ◽  
Land Use Types ◽  
Fuzzy Cellular Automata ◽  
Traffic Guidance

The spatial evolution of land use in Jinzhou area was simulated using fuzzy cellular automata to determine all factors influencing urban land use change. For this purpose, land use data of multiple sources and remote sensing images from 2003 to 2015 were analyzed. The following results were obtained: (1) real land use data and simulation data for 2015 were tested using four indices. Under the 5 m × 5 m scale, the model shows good performance for simulation of areas with various land use types. (2) Among simulations under four scenarios, the effect of traffic guidance on the development of construction land was more distinct under the economic development mode, which clearly showed the phenomenon of “agglomeration” along major traffic lines. (3) Jinshitan Street is adjacent to the sea, and land use changes are significant under the 4th scenario, and thus related departments should pay more attention. (4) Shortcomings of conventional cellular automata model in processing complex systems could be mitigated through the integration of fuzzy sets.

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