Ainong Li

Ainong Li
Institute of Mountain Hazards and Environment,Chinese Academy of Sciences · Research Center for Digital Mountain and Remote Sensing application

PhD

About

172
Publications
44,875
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
3,369
Citations
Citations since 2017
99 Research Items
2732 Citations
20172018201920202021202220230100200300400500600
20172018201920202021202220230100200300400500600
20172018201920202021202220230100200300400500600
20172018201920202021202220230100200300400500600
Introduction
Additional affiliations
January 2012 - July 2017
Chinese Academy of Sciences
Position
  • Managing Director
July 2010 - September 2019
Chinese Academy of Sciences
Position
  • Managing Director

Publications

Publications (172)
Article
Full-text available
The advent of new high-performance cloud computing platforms (e.g., Google Earth Engine (GEE)) and freely available satellite data provides a great opportunity for land cover (LC) mapping over large-scale areas. However, the shortage of reliable and sufficient reference samples still hinders large-scale LC classification. Here, selecting Turkey as...
Article
Full-text available
Land use change (LUC) can be affected by investment growth and planning policies under the context of regional economic cooperation and development. Previous studies on land use simulation mostly emphasized the effects of local socioeconomic factors and planning constraint areas that prevent land conversions. However, investment and national planni...
Article
Full-text available
The fraction of absorbed photosynthetically active radiation (FAPAR) is an essential biophysical variable for monitoring vegetation growth and quantitatively describing the efficiency of light absorption by vegetation. Several long-term global satellite FAPAR products, such as MODIS, GLASS, GEOV2, and GIMMS3g-FAPAR, have been produced at coarse spa...
Article
Water-land ecotone is a core area of wetlands which play an important role in ecological function. The information of vegetation type on the water-land ecotone is important for detecting the health of the wetland, and its protection. Seasonal flooding is a key factor in controlling the environment in water-land ecotone. Even preventing direct detec...
Article
Accurate estimation of mountain vegetation gross primary productivity (GPP) at fine spatial resolutions offers opportunities to better understand mountain ecosystems’ feedback to the global climate system. Eco-hydrological models have great advantages in simulating mountain vegetation photosynthesis, but their large-scale applications remain challe...
Article
Full-text available
A high-quality leaf-area index (LAI) is important for land surface process modeling and vegetation growth monitoring. Although multiple satellite LAI products have been generated, they usually show spatio-temporal discontinuities and are sometimes inconsistent with vegetation growth patterns. A deep-learning model was proposed to retrieve time-seri...
Article
Full-text available
Accurate estimation of gross primary productivity (GPP) is essential for understanding the terrestrial carbon budget. Current large‐scale GPP estimates are often obtained at coarse resolutions without considering the subpixel heterogeneity, leading to scaling errors in results. Here, to further characterize (a) the critical sub‐upscaling process ca...
Article
Full-text available
Topography affects the fraction of scene components of the canopy and background, resulting in the observed reflectance distortion. Modeling the canopy reflectance over rugged terrain needs to account for topographic effects. For this purpose, the existing models greatly increased the mathematical complexity while improving description of terrain a...
Article
Accurate monitoring of gross primary productivity (GPP) is crucial to understanding the feedback to global climate change. Due to the availability of remotely sensed vegetation index (VI) since the 1970s, VI-based models have been an effective tool to obtain spatial-continuous GPP estimates at a large scale. However, most VI-based models neglect th...
Article
Full-text available
地基激光雷达树木点云数据的枝叶分离是精确计算地上生物量和叶面积指数的重要前提, 也是树木三维建模的重要步骤。然而,山地复杂树木冠幅大且结构复杂,从而造成树叶与枝干之间的相互遮挡,因此很难获取高质量的点云数据,目前对其实现枝叶分离依然存在较大的困难。利用地基激光雷达FARO Focus3D X330 获取三维激光点云数据,提出了一种基于网络图的树木点云枝叶分离方法。首先,采用LeWos 模型对点云进行初步的枝叶分离,分离出枝干和叶片点云。在此基础上,针对枝干和叶片混合点云通过路径追踪检测算法来精细分离枝干和叶片。随着路径长度从10 增加到100,枝干点不断增加,叶片点不断减少,枝叶分离精确度、枝干F 分数、叶片F 分数、Kappa 系数均先增加后减少。综合这4 项精度评价指标,选取各个树木最优...
Article
Time series leaf area index (LAI) is essential to studying vegetation dynamics and climate changes. The LAI at current status can be regarded as the accumulative consequence of the counterpart at prior times. Although the deep learning (DL) algorithm, long short-term memory (LSTM), can capture long-time dependencies from sequential satellite data f...
Article
Canopy reflectance models over sloping terrain are critical and reliable tools for vegetation biophysical parameter retrieval. However, the applicability of existing models is strictly limited by individual canopy structure, such as continuous or discontinuous canopies, and hybrid vegetation structure is seldom considered in current models. Therefo...
Article
Full-text available
Vegetation biophysical products offer unique opportunities to examine long-term vegetation dynamics and land surface phenology (LSP). It is important to understand the time-series performances of various global biophysical products for global change research. However, few endeavors have been dedicated to assessing the performances of long-term chan...
Article
Time-series Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary productivity (GPP) has been served as an effective tool to assess the terrestrial carbon budget for the entire globe since 2000. However, the current MODIS GPP product neglects the surface heterogeneity in the modeling process and is always generated at 500 m or 1 km re...
Article
Full-text available
Irrigated agricultural expansion is one of the main reasons for water scarcity in the Lake Urmia basin. Although previous studies have analyzed the impact of cropland expansion on the Lake Urmia Shrinkage, there is a lack of comprehensive annual assessment of historical irrigation expansion in the Lake Urmia basin and its impact on water resources...
Article
Full-text available
Topographic effects in medium and high spatial resolution remote sensing images greatly limit the application of quantitative parameter retrieval and analysis in mountainous areas. Many topographic correction methods have been proposed to reduce such effects. Comparative analyses on topographic correction algorithms have been carried out, some of w...
Article
China-Pakistan economic corridor (CPEC), a critical part of the Belt and Road initiative (BRI), is subjected to rapid infrastructure development, which may lead to potential eco-environmental vulnerability. This study uses multi-source geo-information, and the multi-criteria decision-making (MCDM)-based best–worst method (BWM) to quantify the basel...
Article
Full-text available
Light Use Efficiency (LUE), Vegetation Index (VI)-based, and process-based models are the main approaches for spatially continuous gross primary productivity (GPP) estimation. However, most current GPP models overlook the effects of topography on the vegetation photosynthesis process. Based on the structures of a two-leaf LUE model (TL-LUE), a VI-b...
Article
Full-text available
Previous knowledge of the possible spatial relationships between land cover types is one factor that makes remote sensing image classification “smarter”. In recent years, knowledge graphs, which are based on a graph data structure, have been studied in the community of remote sensing for their ability to build extensible relationships between geogr...
Article
Full-text available
Mountains are undergoing widespread changes caused by human activities and climate change. Given the importance of mountains, the protection and sustainable development of mountain ecosystems have been listed as the goals of the United Nations 2030 Sustainable Development Agenda. As one of the indicators, the Mountain Green Cover Index (MGCI) datas...
Article
Full-text available
Land surface models intended for large‐scale applications are often executed at coarse resolutions, and the sub‐grid heterogeneity is usually ignored. Here, a spatial scaling algorithm that integrates the information of vegetation heterogeneity (land cover type and leaf area index) and surface topography (elevation, slope, relative azimuth (Raz) be...
Article
Full-text available
The impact of global climate change on vegetation has become increasingly prominent over the past several decades. Understanding vegetation change and its response to climate can provide fundamental information for environmental resource management. In recent years, the arid climate and fragile ecosystem have led to great changes in vegetation in Y...
Article
Full-text available
The Three-River Source Region (TRSR) is an important area for the ecological security of China. Vegetation growth has been affected by the climate change, topography, and human activities in this area. However, few studies have focused on analyzing time series tendencies of vegetation change in various terrain conditions. To address this issue in t...
Article
Full-text available
Large-scale projects, such as the construction of railways and highways , usually cause an extensive Land Use Land Cover Change (LULCC). The China-Central Asia-West Asia Economic Corridor (CCAWAEC), one key large-scale project of the Belt and Road Initiative (BRI), covers a region that is home to more than 1.6 billion people. Although numerous stud...
Article
Full-text available
Bangladesh-China-India-Myanmar economic corridor, a critical part of the Belt and Road Initiative program, is subject to the impact of various natural disasters and intense human activities, which have led to serious ecological vulnerability. This study proposed a prototype model using geographically weighted principal component analysis to quantif...
Article
Full-text available
Forests have significant impacts on the global carbon cycle, hydrological processes, and biodiversity. Driven by socioeconomic developments, forests experienced drastic changes since the mid-20th century in China. Although declassified spy satellite and other Earth observation satellite data offer remote sensing technologies for mapping these long-...
Article
The temperature and greenness model (TG) demonstrates that the combination of enhanced vegetation index and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) is feasible in obtaining gross primary productivity (GPP) at the landscape, regional, and global scales. However, the input LST data of TG is always availabl...
Article
Full-text available
Distribution of Land Cover (LC) classes is mostly imbalanced with some majority LC classes dominating against minority classes in mountainous areas. Although standard Machine Learning (ML) classifiers can achieve high accuracies for majority classes, they largely fail to provide reasonable accuracies for minority classes. This is mainly due to the...
Article
Full-text available
The Land Cover Classification System (LCCS) is a fundamental element and representative feature for any Land Cover Data Set (LCDS). Although various LCCSs have been proposed during the past few decades, discrepancies of LCCSs have widely existed in various LCDSs, which have caused negative impacts on comprehensive comparison and integrated utilizat...
Article
Full-text available
Recently, light use efficiency (LUE) models have been widely used for calculating gross primary productivity (GPP). Unfortunately, these models are only suitable for flat areas without considering the topographic effects on plant photosynthesis. In this study, considering the topographic controls on direct radiation, diffuse radiation, and sunlit c...
Article
This study was carried out about two years after a major landslide took place in Aranayake, Sri Lanka to evaluate geo-ecological status quo (spatial variation of vegetation and geo-environmental variables, and the correlations between them), and to identify spatially explicit landscape units (ecotopes). Sampling was done continuously based on a mes...
Article
Full-text available
Grazing intensity (GI) is an important indicator for grazing situations in pastoral areas. However, it has been difficult to be observed directly in the field, due to the randomness and dynamics of the grazing behavior of livestock. Consequently, the lack of actual GI information has become a common issue in studies on quantitatively estimating GI....
Article
Mountains provide essential ecosystem services to billions of people and are home to a majority of the global biodiversity hotspots. However, mountain ecosystems are particularly sensitive to climate and environmental changes. The protection and sustainable management of mountain ecosystems are thus of great importance and are listed as a Sustainab...
Article
Full-text available
Land cover samples are usually the foundation for supervised classification. Unfortunately, for land cover mapping in large areas, only limited samples can be used due to the time-consuming and labor-intensive sample collection. A novel and practical Object-oriented Iterative Classification method based on Multiple Classifiers Ensemble (OIC-MCE) wa...
Article
Full-text available
Land use reflects human activities on land. Urban land use is the highest level human alteration on Earth, and it is rapidly changing due to population increase and urbanization. Urban areas have widespread effects on local hydrology, climate, biodiversity, and food production. However, maps, that contain knowledge on the distribution, pattern and...
Chapter
Full-text available
In the promotion of economic digitalization as an important force driving the realization of development through innovation, countries around the world have made forward-looking arrangements in frontier technology research and development, open data for sharing, privacy security protection, and personnel training. China also attaches great importan...
Article
Full-text available
As a key parameter that represents the structural characteristics and biophysical changes of crop canopy, the leaf area index (LAI) plays a significant role in monitoring crop growth and mapping yield. A considerable amount of farmland is dispersed with strong spatial heterogeneity. The existing time series satellite LAI products fail to capture sp...
Article
Background climate and socio-economy significantly affect the landscape dynamics of natural ecosystem. And the simulated method to understand the landscape dynamics of natural ecosystems in responding to human and natural effects is increasingly important for ecosystem management. In this study, we integrated system dynamics, MaxEnt and cellular aut...
Article
Hyperspectral remote sensing is economical and fast, and it can reveal detailed spectral information of plants. Hence, hyperspectral data are used in this study to analyse the spectral anomaly behaviours of vegetation in porphyry copper mine areas. This analytical method is used to compare the leaf spectra and relative differences among the vegetat...
Article
Full-text available
Local topography significantly affects remotely sensed reflectance data and subsequently impacts leaf area index (LAI) retrieval over mountainous areas. Therefore, mountain vegetation LAI mapping from satellite observations at multiple scale levels is often obstructed by topographic distortion. To analyze the effects of topography on multiresolutio...
Article
Full-text available
The estimation of aboveground biomass (AGB), an important indicator of grassland production, is crucial for evaluating livestock carrying capacity, understanding the response and feedback to climate change, and achieving sustainable development. Most existing grassland AGB estimation studies were based on empirical methods, in which field measureme...
Article
Ecosystem models have been widely used for obtaining gross primary productivity (GPP) estimations at multiple scales. Leaf area index (LAI) is a critical variable in these models for describing the vegetation canopy structure and predicting vegetation-atmosphere interactions. However, the uncertainties in LAI datasets and the effects of their repre...
Article
Fine spatial details of vegetation growth are usually lost in leaf area index (LAI) products obtained from coarse spatial resolution satellite sensors. This may bring uncertainties in ecosystem process models, which usually require LAI products with fine spatiotemporal resolutions. Successful downscaling of LAI dynamics to fine spatial resolution i...
Article
Full-text available
The Research Center for Digital Mountain and Remote Sensing Application at the Institute of Mountain Hazards and Environment (IMHE), Chinese Academy of Sciences (CAS), is a research unit specially focusing on developing key geospatial techniques based on geographic information systems and remote sensing methods. The purpose of this research is to d...
Article
Full-text available
The scientific community has widely reported the impacts of climate change on the Central Himalaya. To qualify and quantify these effects, long-term land surface temperature observations in both the daytime and nighttime, acquired by the Moderate Resolution Imaging Spectroradiometer from 2000 to 2017, were used in this study to investigate the spat...
Article
Ecosystems are at risk of environmental degradation by the intensification of human activities and climate change over the world. This manuscript aims to present a systematic and direct methodology for abiotic risk assessment. In this study, a novel ecological risk assessment index called “performance relative severity index” (PRS) was developed to...
Article
Full-text available
The South Asia has high variability in geographical features, climate, and landscapes. With the rapid economic development and population growth, the increased pressure on natural resources, land degradation, water crisis, and climate change become the common concerns for the countries in the region. To get a deep and general idea about the land an...
Article
Quantitatively evaluating vegetation cooling service has become an important issue in current ecosystem service assessment, especially for urban area. Based on a previous method proposed on the energy exchanging theory, this study developed an improved method to generate a spatially explicit evaluation of the vegetation cooling service by introduci...
Article
Photosynthesis plays an important role in terrestrial carbon cycle, and simulation of photosynthesis through terrestrial biosphere models usually requires a specification of maximum carboxylation rate (Vcmax). However, estimating Vcmax by gas-exchange experiments is laborious and tedious, resulting in a general paucity of Vcmax data. In this study,...
Article
Rugged terrain distorts optical remote sensing signals, and land-cover classification and biophysical parameter retrieval over mountainous regions must account for topographic effects. Therefore, topographic correction is a prerequisite for many remote sensing applications. In this study, we proposed a semi-physically based and simple topographic c...
Article
With the launch of the Joint Polar Satellite System (JPSS)/Soumi National Polar-orbiting Partnership (S-NPP) satellite in October 2011, the need for the operational monitoring of terrestrial processes at the regional and global scales led to the expansion of terrestrial remote sensing products (e.g., the clear-sky composited surface reflectance pro...
Article
Full-text available
Developing effective policies for biodiversity conservation and restoration policies requires spatially and temporally explicit data on distribution of species and habitats. Remote sensing provides an effective technical tool to meet this requirement. In recent years, the rapid development of integrated multi-platform, multi-scale, multi-mode remot...
Article
The low-resolution characteristic of passive microwave surface soil moisture (SSM) products greatly limits their application in many fields at regional or local scale. Aiming to overcome this limitation, a random forest (RF)-based downscaling approach was proposed in this study to disaggregate the Soil Moisture Active and Passive (SMAP) SSM product...
Article
Full-text available
Spatiotemporal fusion (STF) technologies are commonly used to acquire high spatiotemporal resolution remote sensing observations. However, most STF technologies fail to consider the nonlinear variation in vegetation in the time domain. Based on the Best Linear Unbiased Estimator (BLUE), this paper proposed a novel STF algorithm (referred to BLUE) w...