Tim Van de Voorde

Ghent University | UGhent · Department of Geography

Effective management of agricultural water resources in arid regions relies on precise estimation of irrigation-water demand. Most previous studies have adopted pixel-level mapping methods to estimate irrigation-water demand, often leading to inaccuracies when applied in arid areas where land salinization is severe and where poorly growing crops ca...

Thin cloud interference presents a significant challenge for the semantic segmentation of optical satellite imagery, which directly degrades the model accuracy and causes difficulties in sample selection. This paper generated a dataset named Populus euphratica and Tamarix chinensis discrimination (PTD), containing both cloudless and thin cloud scen...

Temperature and precipitation are crucial indicators for investigating climate changes, necessitating precise measurements for rigorous scientific inquiry. While the Fifth Generation of European Centre for Medium-Range Weather Forecasts Atmospheric Reanalysis (ERA5), ERA5 of the Land Surface (ERA5-Land), and China Meteorological Forcing Dataset (CM...

Detecting individual Populus euphratica (P. euphratica) trees in desert forest areas is crucial for monitoring their ecophysiological characteristics and ecological conservation. However, the presence of the spectral-similar Tamarix chinensis (T. chinensis) in the habitats, along with the densely overlapping crowns in clustered P. euphratica...

Climate change and human activities increasingly impact watershed ecological quality (EQ), particularly in large transboundary watersheds. This study introduces an amended Water Benefit-Based Ecological Index (AWBEI) to assess changes in EQ within the Irtysh River Basin (IRB) from 2000 to 2023. AWBEI integrates indicators like surface water abundan...

In the context of global warming, an increase in atmospheric aridity and global dryland expansion under the future climate has been expected in previous studies. However, this conflicts with observed greening over drylands and the insignificant increase in hydrological and ecological aridity from the ecohydrology perspective. Combining climatic, hy...

Reducing soil salinization of croplands with optimized irrigation and water management is essential to achieve land degradation neutralization (LDN). The effectiveness and sustainability of various irrigation and water management measures to reduce basin-scale salinization remain uncertain. Here we used remote sensing to estimate the soil salinity...

Using statistical methods that do not directly represent the causality between variables to attribute climate and plant traits as controlling ecosystem functions may lead to biased perceptions. We revisited this issue using a causal graphical model, the Bayesian network (BN), capable of quantifying causality by conditional probability tables. Based...

In the context of global warming, an increase in atmospheric aridity and global dryland expansion were expected under the future climate in previous studies. However, it conflicts with observed greening over drylands and the insignificant increase in hydrological and ecological aridity from the ecohydrology perspective. Combining climatic, hydrolog...

The surface water area and types in the Aral Sea Basin (ASB) have undergone extensive changes due to the impacts of climate change and anthropogenic activities. This study explores the changes in the surface water area in the ASB based on the Google Earth Engine cloud platform. Then, we integrate multi-source data to identify 1559 lakes and 196 res...

With the emergence of multisource data and the development of cloud computing platforms, accurate prediction of event-scale dust source regions based on machine learning (ML) methods should be considered, especially accounting for the temporal variability in sample and predictor variables. Arid Central Asia (ACA) is recognized as one of the world’s...

Reanalysis and remotely sensed soil moisture (SM) products are important for monitoring hydrology and the terrestrial carbon cycle, especially in water-limited arid regions. However, it is essential to assess the reliability of SM products before they are used. In this study, surface SM from the European Reanalysis-Interim v5 (ERA5), Essential Clim...

The Kunlun–Pamir Plateau is a globally irreplaceable biodiversity reserve, yet it is still unclear what causes the distribution of species richness. Here, we relied on the productivity and the water–energy dynamics hypotheses to investigate the distribution pattern of species richness (and its determinants) in the Kunlun–Pamir Plateau. The producti...

With the increasing maturity of big data technology, its application in the field of environmental assessment has become an important issue. The mining of mineral resource can affect the balance in the ecological environment surrounding mining areas and the normal life activities of humans through groundwater. To solve this problem, big data-based...

Urban parks are important public places that provide an opportunity for city dwellers to interact with nature. In recent years, social media data have become a promising data source for the assessment of cultural ecosystem services (CES) and landscape features in urban parks. However, it is a challenging task to identify and classify the CES and la...

Soil moisture (SM) is essential for controlling terrestrial carbon uptake, as it directly provides moisture for photosynthesis, especially in arid and semiarid regions. We selected the arid and semiarid Ili River basin (IRB) of Xinjiang as the study area, and investigated the spatial and temporal characteristics and interrelationships with SM and p...

The discharge of wastewater and waste rock in mining production activities is a significant hidden cause of soil heavy metal pollution. The accumulation of heavy metals in soil occurs through a variety of processes, and exposure to these metals can permanently damage the human body. Due to multiple factors, such as the formation causes, sources, an...

The recession of the South Aral Sea over the last few decades has become a great environmental challenge in Central Asia. Due to declining inflow and irrigation exhaustion, the Amu Darya River vanishes before reaching the South Aral Sea. Therefore, groundwater (GW) has become the vital water source for the South Aral Sea surface water and the local...

With the rapid accumulation of water flux observations from global eddy-covariance flux sites, many studies have used data-driven approaches to model water fluxes, with various predictors and machine learning algorithms used. However, it is unclear how various model features affect prediction accuracy. To fill this gap, we evaluated this issue base...

Using statistical methods that do not emphasize the systematic causality to attribute climate and plant traits to control ecosystem function may produce biased perceptions. We revisit this issue using a Bayesian network (BN) capable of quantifying causality. Based on expert knowledge and climate, vegetation, and ecosystem function data from the FLU...

Sand and dust storms (SDS) are both symptoms and causes of desertification. As one of the essential parts of desertification control, SDS source identification can be readily carried out using remote sensing data. This letter proposes an automatic SDS source identification method based on ERA5 surface wind direction and MODIS daily surface reflecta...

Net ecosystem exchange (NEE) is an important indicator of carbon cycling in terrestrial ecosystems. Many previous studies have combined flux observations and meteorological, biophysical, and ancillary predictors using machine learning to simulate the site-scale NEE. However, systematic evaluation of the performance of such models is limited. Theref...

Accurate sand and dust storm (SDS) detection is important for assessing SDS disaster risk. Machine learning (ML) based SDS detection approaches have been widely used in recent years due to their higher accuracy and better detection results. However, this approach usually requires manual annotation of numerous training samples that are, in practice,...

The massive desiccation of the Aral Sea, the fourth largest lake in the world, has led to severe ecological problems, expansion of cropland was thought to be the main factor driving that shrinkage. But this study performed a long-term land cover and use change assessment for Aral Sea Basin (ASB) to show that the cropland has stopped expanding in 20...

As the Aral Sea shrinks, the lakebeds are gradually drying up, and the newborn Aralkum Desert (AD) has become one of the most active sands and dust storms (SDS) sources in Arid Central Asia (ACA). However, the temporal characterization of SDS activity and its possible driving factors have yet to be thoroughly investigated. Here, we studied the temp...

As the Aral Sea shrinks, the lakebeds are gradually drying up, and the newborn Aralkum Desert (AD) has become one of the most active sands and dust storms (SDS) sources in Arid Central Asia (ACA). However, the temporal characterization of SDS activity and its possible driving factors have yet to be thoroughly investigated. Here, we studied the temp...

With the rapid accumulation of water flux observations from global eddy-covariance flux sites, many studies have used data-driven approaches to model site-scale water fluxes with various predictors and machine learning algorithms used. However, systematic evaluation of such models is still limited. We therefore performed a meta-analysis of 32 such...

Net ecosystem exchange (NEE) is an important indicator of carbon cycling in terrestrial ecosystems. Many previous studies have combined flux observations, meteorological, biophysical, and ancillary predictors using machine learning to simulate the site-scale NEE. However, systematic evaluation of the performance of such models is limited. Therefore...

Assessing the perceptions of urban parks and understanding the relationships between environmental features and park perceptions are critical to the design and management of urban parks. However, it is challenging to quantify park perceptions at a large spatial-temporal scale. In addition, little is known about which environmental features contribu...

Assessing the perceptions of urban parks and understanding the relationships between environmental features and park perceptions are critical to the design and management of urban parks. However, it is challenging to quantify park perceptions at a large spatial-temporal scale. In addition, little is known about which environmental features contribu...

The rapid growth of Earth observation (EO) data poses a challenge to the way of data management. An efficient framework based on big data technology can bring new solutions. Some excellent frameworks have been proposed, which provide efficient organization and management of EO data. However, they are not optimized for data distribution in the stora...

Understanding the impacts of environmental factors on spatial–temporal and large-scale rodent distribution is important for rodent damage prevention. Investigating rat hole density (RHD) is one of the most effective methods to obtain the intensity of rodent damage. However, most of the previous field surveys or UAV-based remote sensing methods can...

Ecosystem services (ESs) provided by the major basins of Central Asia are critical to human well-being and have attracted the attention of the international community. The identification of conservation priorities is of great significance for the maintenance and protection of key ESs. In this study, we quantified the spatiotemporal changes of net p...

Spatiotemporal characteristics of the trade-off among ecosystem services and its mechanism have been extensively studied. However, studies on the difference in spatiotemporal variation of ecosystem services trade-offs in various climate zones under climate change are limited. This study aims to explore the spatiotemporal characteristics and driving...

Extreme rainfall events are rare in inland arid regions, but have exhibited an increasing trend in recent years, causing many casualties and substantial socioeconomic losses. A series of heavy rains that began on July 31th, 2018, battered the Hami prefecture of eastern Xinjiang, China for four days. These rains sparked devastating floods, caused 20...

Global climate change and human activities are expected to have far-reaching implications for the associations between ecosystem services (ESs), especially in arid regions. Here, Central Asia (CA) was taken as a case study to describe the complex relationship among key ESs under the combined effects of future climate change and socioeconomic develo...

Despite the growing interest among researchers, satellite-based prediction of soil salinity remains highly uncertain. The improvements in prediction accuracy reported in previous studies are usually limited to a single area. We performed a meta-analysis of regional satellite-based soil salinity predictions combined with in situ soil sampling and...

The spatial calculation of vector data is crucial for geochemical analysis in geological big data. However, large volumes of geochemical data make for inefficient management. Therefore, this study proposed a shapefile storage method based on MongoDB in GeoJSON form (SSMG) and a shapefile storage method based on PostgreSQL with open location code (O...

Extreme precipitation events exhibit an increasing trend for both the frequency and magnitude on global and regional scales and it has already proven the impact of man-made global warming on the extreme precipitation amplification. Based on the observed datasets and global climate model (GCM) output, this study has evaluated the impact from anthrop...

The Altai Mountains are one of the most impressive and valuable archaeological areas in the world. Kurgans (burial mounds) of ancient civilizations, which are scattered across the vast Altai area, are an exceptionally valuable source of information for archaeology. These precious archaeological resources, which sometimes have been preserved intact...

Citation: Guo, Z.; Kurban, A.; Ablekim, A.; Wu, S.; Van de Voorde, T.; Azadi, H.; Maeyer, P.D.; Dufatanye Umwall, E. Estimation of Photosynthetic and Non-Photosynthetic Vegetation Coverage in the Lower Reaches of Tarim River Based on Sentinel-2A Data.

The previous comparative studies on watersheds were mostly based on the comparison of dispersive characteristics, which lacked systemicity and causality. We proposed a causal structure-based framework for basin comparison based on the Bayesian network (BN) and focus on the basin-scale water–energy–food–ecology (WEFE) nexus. We applied it to the Syr...

Technology is transforming societies worldwide. A major innovation is the emergence of robotics and autonomous systems (RAS), which have the potential to revolutionize cities for both people and nature. Nonetheless, the opportunities and challenges associated with RAS for urban ecosystems have yet to be considered systematically. Here, we report th...

In this short communication, we describe the shortcomings and pitfalls of a commonly used method to detect ground materials that relies on setting thresholds for normalized difference indices. We analyze this method critically and present some experimental results on the USGS and ECOSTRESS spectral libraries and on real Sentinel-2 and Landsat-8 ima...

Technology is transforming societies worldwide. A major innovation is the emergence of robotics and autonomous systems (RAS), which have the potential to revolutionize cities for both people and nature. Nonetheless, the opportunities and challenges associated with RAS for urban ecosystems have yet to be considered systematically. Here, we report th...

The previous comparative studies on watersheds were mostly based on the comparison of dispersive characteristics, which lacked systemicity and causality. We proposed a causal structure-based framework for basin comparison based on the Bayesian network (BN), and focus on the basin-scale water-energy-food-ecology (WEFE) nexuses. We applied it to the...

It is speculated that floods in many areas of the world have become more severe with global warming. This study describes the 2017 spring floods in Kazakhstan, which, with about six people dead or missing, prompted the government to call for more than 7,000 people to leave their homes. Then, based on the Climatic Research Unit (CRU), the NCEP/NCAR...

Agriculture is one of the most critical sectors of the Mongolian economy. In Mongolia, land degradation is increasing in the cropland region, especially in a cultivated area. The country has challenges to identify new croplands with sufficient capacity for cultivation, especially for local decision-makers. GIS applications tremendously help science...

Due to the fragmented compositional structure of urban scenes, many pixels are mixtures of multiple materials even in high spatial resolution airborne hyperspectral data. In the past ten years, sparse regression based spectral unmixing methods have achieved some noticeable results. Recently, Chen et al. proposed a jointly sparse spectral mixture an...

Commonly applied water indices such as the normalized difference water index (NDWI) and the modified normalized difference water index (MNDWI) were originally conceived for medium spatial resolution remote sensing images. In recent decades, high spatial resolution imagery has shown considerable potential for deriving accurate land cover maps of urb...

Water resources are increasingly under stress in Central Asia because downstream countries are highly dependent on upstream countries. Water is essential for irrigation and is becoming scarcer due to climate change and human activities. Based on 20 hydrological stations, this study firstly analyzed the annual and seasonal spatial–temporal changes o...

High spatial resolution hyperspectral imagery has shown considerable potential for deriving accurate land cover maps in urban areas. In this paper, a new classification framework for mapping land cover in urban environ- ments using high spatial resolution hyperspectral data was proposed. The proposed classification scheme was applied to map urban l...

Fast and automatic detection of airports from remote sensing images is useful for many military and civilian applications. In this paper, a fast automatic detection method is proposed to detect airports from remote sensing images based on convolutional neural networks using the Faster R-CNN algorithm. This method first applies a convolutional neura...

In remote sensing data exploitation, spectral mixture analysis is commonly used to detect land cover materials and their corresponding proportions present in the observed scene. In recent years, high spatial resolution airborne hyperspectral images have shown their potential for deriving accurate land cover maps. In this paper, a new spectral mixtu...

Cities often have a substantial green infrastructure, which provides local ecosystem services that improve the quality of life of urban residents. These services should be explicitly addressed in urban development policies, and areas with insufficient vegetation and limited access to public green spaces should be identified. This paper presents two...

Land use change models are powerful tools that allow planners and policy makers to assess the long-term spatial and environmental impacts of their decisions. In order for these models to produce a realistic output, they should be properly calibrated. This is usually achieved by comparing simulated land-use maps of dates in the past to reference lan...

Land-use/land-cover information constitutes an important component in the calibration of many urban growth models. Typically, the model building involves a process of historic calibration based on time series of land-use maps. Medium-resolution satellite imagery is an interesting source for obtaining data on land-use change, yet inferring informati...

A recently concluded research project called Measuring and Modelling Urban Dynamics (MAMUD), funded by Belspo, investigated how high and moderate resolution satellite imagery can be used for mapping and modeling urban growth and its impact on the hydrology of the urban and suburban environment. In this paper, some of the research methods and major...