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| 1 | 40-Year(1978–2017) human settlement changes in China reflected by impervious surfaces from satellite remote sensing显示文摘Impervious surfaces are the most significant feature of human settlements. Timely, accurate, and frequent information on impervious surfaces is critical in both social-economic and natural environment applications. Over the past 40 years, impervious surface areas in China have grown rapidly. However,annual maps of impervious areas in China with high spatial details do not exist during this period. In this paper, we made use of reliable impervious surface mapping algorithms that we published before and the Google Earth Engine(GEE) platform to address this data gap. With available data in GEE, we were able to map impervious surfaces over the entire country circa 1978, and during 1985–2017 at an annual frequency. The 1978 data were at 60-m resolution, while the 1985–2017 data were in 30-m resolution.For the 30-m resolution data, we evaluated the accuracies for 1985, 1990, 1995, 2000, 2005, 2010, and2015. Overall accuracies reached more than 90%. Our results indicate that the growth of impervious surface in China was not only fast but also considerably exceeding the per capita impervious surface area in developed countries like Japan. The 40-year continuous and consistent impervious surface distribution data in China would generate widespread interests in the research and policy-making community. The impervious surface data can be freely downloaded from http://gffzze48ac8bb440f4181hnxcv9bw0c0qc6owp.ffgz.tsg.suse.edu.cn. | Peng Gong Xuecao Li Wei Zhang | 2019 | Science Bulletin2019，64，11： | 93 |
| 2 | A multi-resolution global land cover dataset through multisource data aggregation显示文摘Recent developments of 30 m global land characterization datasets(e.g., land cover, vegetation continues field) represent the finest spatial resolution inputs for global scale studies. Here, we present results from further improvement to land cover mapping and impact analysis of spatial resolution on area estimation for different land cover types. We proposed a set of methods to aggregate two existing 30 m resolution circa 2010 global land cover maps, namely FROM-GLC(Finer Resolution Observation and Monitoring-Global Land Cover) and FROM-GLC-seg(Segmentation), with two coarser resolution global maps on development, i.e., Nighttime Light Impervious Surface Area(NL-ISA) and MODIS urban extent(MODIS-urban), to produce an improved 30 m global land cover map—FROM-GLC-agg(Aggregation). It was post-processed using additional coarse resolution datasets(i.e., MCD12Q1, GlobCover2009, MOD44 W etc.) to reduce land cover type confusion. Around 98.9% pixels remain 30 m resolution after some post-processing to this dataset. Based on this map, majority aggregation and proportion aggregation approaches were employed to create a multi-resolution hierarchy(i.e., 250 m, 500 m, 1 km, 5 km, 10 km, 25 km, 50 km, 100 km) of land cover maps to meet requirements for different resolutions from different applications. Through accuracy assessment, we found that the best overall accuracies for the post-processed base map(at 30 m) and the three maps subsequently aggregated at 250 m, 500 m, 1 km resolutions are 69.50%, 76.65%, 74.65%, and 73.47%, respectively. Our analysis of area-estimation biases for different land cover types at different resolutions suggests that maps at coarser than 5 km resolution contain at least 5% area estimation error for most land cover types. Proportion layers, which contain precise information on land cover percentage, are suggested for use when coarser resolution land cover data are required. | YU Le WANG Jie LI XueCao LI CongCong ZHAO YuanYuan GONG Peng | 2014 | Science China Earth Sciences2014，57，10： | 24 |
| 3 | The first all-season sample set for mapping global land cover with Landsat-8 data显示文摘We report the world's first all-season training and validation sample sets for global land cover classification with Landsat-8 data.Prior to this,such samples were only available at a single date primarily from the growing season.It is unknown how much limitation such a single-date sample has to mapping global land cover in other seasons of the year.To answer this question,we selected available Landsat-8 images from four seasons and collected training and validation samples from them.We compared the performances of training samples in different seasons using Random Forest algorithm.We found that the use of training samples from any individual season would result in the best overall classification accuracy when validated by samples in the same season.The global overall accuracy from combined best seasonal results was 67.2% when classifying the 11 Level-1 classes in the Finer Resolution Observation and Monitoring of Global Land Cover(FROM-GLC) classification system.The use of training samples from all seasons(named all-season training sample set hereafter) produced an overall accuracy of 67.0%.We also tested classification within 10° latitude 60° longitude zones using all-season training subsample within each zone and obtained an overall accuracy of 70.2%.This indicates that properly grouped subsamples in space can help improve classification accuracies.All the results in this study seem to suggest that it is possible to use an all-season training sample set to reach global optimality with universal applicability in classifying images acquired at any time of a year for global land cover mapping. | Congcong Li Peng Gong Jie Wang Zhiliang Zhu Gregory S. Biging Cui Yuan Tengyun Hu Haiying Zhang Qi Wang Xuecao Li Xiaoxuan Liu Yidi Xu Jing Guo Caixia Liu Kwame O. Hackman Meinan Zhang Yuqi Cheng Le Yu Jun Yang Huabing Huang Nicholas Clinton | 2017 | Science Bulletin2017，62，7： | 21 |
| 4 | Urban growth models: progress and perspective显示文摘城市的生长模型被开发了并且广泛地采用了在周围的环境上学习城市的扩大和它的影响。这些模特儿能在发展情形的城市的决策或分析被雇用。在这份报纸,我们提供城市的生长模型的系统的评论,包括城市的模型和联系理论和不同模型和他们的应用程序的普通框架的进化。城市的生长的三个典型的班也就是,为陆地使用 / 交通模型,细胞的自动机(CA ) 模型和基于代理人的模型建模,被介绍。他们的关系被解释,就他们的建模机制,数据要求和应用程序规模而言。基于广泛地利用的城市的 CA 模型,我们为改进建议了四个观点包括基本空间单位的调整,时间的上下文,支持模型比较的公共平台,和情形的加入分析。新机会(例如,开的社会数据和综合评价当模特儿) 出现了帮助模型开发和申请。 | Xuecao Li P. Gong | 2016 | Science Bulletin2016，61，21： | 15 |
| 5 | Ten years after Hurricane Katrina: monitoring recovery in New Orleans and the surrounding areas using remote sensing显示文摘Remote sensing data have been widely used in pre-hazard prevention/preparation, emergency response and post-hazard recovery monitoring. Hurricane Katrina caused serious damage to the environment, society and economy in the southern United States in 2005. On the 10 th anniversary of Hurricane Katrina, we monitored the recovery process in New Orleans and the surrounding area based on remote sensing. Results from multi-source remote sensing data indicated that the average vegetation conditions of the affected areas have not fully recovered compared with the pre-disaster conditions, especially in the hurricane's landfall area. Analysis from moderate resolution Landsat data showed that many civil engineering works have been undertaken in the city of New Orleans to prevent future disasters. Frequent observation using highresolution images recorded the progress of some of these civil construction projects(e.g. the 17 th Street Canal pumping station) in New Orleans. In this case study, we illustrated the capabilities of remote sensing techniques in recovery monitoring following a natural disaster. International/institutional cooperation is suggested to improve Earth observation capability in hazard monitoring. More Chinese Earth observation data are expected to be used in international monitoring. | Xuecao Li Le Yu Yidi Xu Jun Yang Peng Gong | 2016 | Science Bulletin2016，61，18： | 2 |
| 6 | Using a global reference sample set and a cropland map for area estimation in China显示文摘A technically transparent and freely available reference sample set for validation of global land cover mapping was recently established to assess the accuracies of land cover maps with multiple resolutions.This sample set can be used to estimate areas because of its equal-area hexagon-based sampling design.The capabilities of these sample set-based area estimates for cropland were investigated in this paper.A 30-m cropland map for China was consolidated using three thematic maps(cropland,forest and wetland maps)to reduce confusion between cropland and forest/wetland.We compared three area estimation methods using the sample set and the 30 m cropland map.The methods investigated were:(1)pixel counting from a complete coverage map,(2)direct estimation from reference samples,and(3)model-assisted estimation combining the map with samples.Our results indicated that all three methods produced generally consistent estimates which agreed with cropland area measured from an independent national land use dataset.Areas estimated from the reference sample set were less biased by comparing with a National Land Use Dataset of China(NLUD-C).This study indicates that the reference sample set can be used as an alternative source to estimate areas over large regions. | YULe LI XueCao LI CongCong ZHAO YuanYuan NIU ZhenGuo HUANG HuaBing WANG Jie CHENG YuQi LU Hui SI YaLi YU ChaoQing FU HaoHuan GONG Peng | 2017 | Science China Earth Sciences2017，60，2： | 1 |
| 7 | Evaluating the effect of plain afforestation project and future spatial suitability in Beijing显示文摘Taking the'One Million-Mu(666 km^2)'Plain Afforestation(PhaseⅠ)Project(Phase I afforestation)in Beijing city as an example,we monitored the growth status of planted forest using long-term remote sensing images,and evaluated the impacts of afforestation on land use change and vegetation growth.We found there is a large space for improvement regarding the ecological benefits of the project.Moreover,we found forest patches with decreasing greenness after the afforestation were mainly converted from farmland with high greenness and low heterogeneity in terms of the normalized difference vegetation index(NDVI).This implies that those farmland patches are inappropriate for afforestation.According to the results from PhaseⅠafforestation and the impact of urbanization on green space,we constructed a series of spatial variables and generated a suitability map for the next'New Round of One Million-Mu(666 km^2)Afforestation project'(PhaseⅡafforestation).We then modeled the spatial distribution of PhaseⅡafforestation based on the derived suitability map.This study is crucial for the scientific evaluation of afforestation projects for space planning(e.g.,urban green space planning).The evaluation and modeling framework built in this study can be used to support the decision making and policy implementation of afforestation projects in China. | Tengyun HU Xuecao LI Peng GONG Wencheng YU Xiaochun HUANG | 2020 | Science China Earth Sciences2020，63，10： | 1 |
| 8 | An improved urban cellular automata model by using the trend-adjusted neighborhood显示文摘Background:Cellular automata(CA)-based models have been extensively used in urban sprawl modeling.Presently,most studies focused on the improvement of spatial representation in the modeling,with limited efforts for considering the temporal context of urban sprawl.In this paper,we developed a Logistic-Trend-CA model by proposing a trend-adjusted neighborhood as a weighting factor using the information of historical urban sprawl and integrating this factor in the commonly used Logistic-CA model.We applied the developed model in the Beijing-Tianjin-Hebei region of China and analyzed the model performance to the start year,the suitability surface,and the neighborhood size.Results:Our results indicate the proposed Logistic-Trend-CA model outperforms the traditional Logistic-CA model significantly,resulting in about 18%and 14%improvements in modeling urban sprawl at medium(1 km)and fine(30 m)resolutions,respectively.The proposed Logistic-Trend-CA model is more suitable for urban sprawl modeling over a long temporal interval than the traditional Logistic-CA model.In addition,this new model is not sensitive to the suitability surface calibrated from different periods and spaces,and its performance decreases with the increase of the neighborhood size.Conclusion:The proposed model shows potential for modeling future urban sprawl spanning a long period at regional and global scales. | Xuecao Li Yuyu Zhou Wei Chen | 2020 | Ecological Processes2020，9，1： | 0 |
| 9 | Analysis of geo-spatiotemporal data using machine learning algorithms and reliability enhancement for urbanization decision support显示文摘We present systematic analyses of the temporal dynamics of the growth of Kumasi,the fastest growing city in Ghana using 20-year Landsat timeseries data from 2000 to 2020(with 1986 Landsat image as a baseline).Two classification algorithms–random forest(RF)and support vector machines(SVM)–were used to produce binary(built-up/non-built up)maps for all years within the temporal span.We further implemented an anomaly detection and temporal consistency algorithm followed by a changing logic to correct the classification anomalies due to image contamination from the cloud and other sources.The mean overall accuracies obtained for RF and SVM were 94.9%(kappa=0.90)and 95.5%(kappa=0.91),respectively.Our results reveal that the mean builtup area percentages of the metropolis are approximately 74,65,47,and 23 for the years 2020,2010,2000,and 1986,respectively,representing a mean annual change of 3.5%over the 34 years.With the present lack of labeled data in Ghana for in-depth analyses of the evolution of land use,we believe that this study serves as an initial attempt to a better understanding of the effects of increasing anthropogenic activities due to urbanization,on human and environment health. | Kwame O.Hackman Xuecao Li Daniel Asenso-Gyambibi Emmanuella A.Asamoah Isaac.D.Nelson | 2020 | International Journal of Digital Earth2020，13，12： | 0 |
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