Xiufeng Wang

Hokkaido University | Hokudai · Research Faculty of Agriculture

In this study, we integrated a remote-sensing fire product (MOD14A1) and land-use product (MCD12Q1) to extract the number of crop-residue burning (CRB) spots and the fire radiative power (FRP) in China from 2001 to 2018. Moreover, we conducted three trend analyses and two geographic distribution analyses to quantify the interannual variations and s...

A quantitative understanding of the global gross primary productivity (GPP) and its responses to increasing CO2 levels is critical for quantifying the feedbacks of ecosystems to climate change. This study applied the daily boreal ecosystem productivity simulator (BEPSd) model to estimate the global GPP from 2000 to 2015, compare the estimated GPP w...

2 There is a demand for better information on forest biomass in tropical regions for use in carbon accounting. This needs robust above-ground biomass (AGB) estimation in different forest types. This study sought to improve biomass estimation by selecting the best regression models based on observations of the contribution of radar signals to AGB in...

We comprehensively integrated various remote sensing, modeling and meteorological datasets to assess and quantify the effects of Indonesia's forest fires in 2015 on the ambient atmosphere. When the forest fires occurred, the fire spots in Sumatra and Borneo increased sharply to 78,055 and fire radiative power (FRP) rose to 4.05 × 10⁶ MW in Septembe...

This paper presents a crop classification method using synthetic aperture radar (SAR) satellite data for mapping, in place of existing ground surveys. We used TerraSAR-X X-band dual-polarization data and RADARSAT-2 C-band full-polarization data. Values of the sigma-naught and polarimetric parameters were calculated from each type of data. We assess...

Optical remote sensing is one of the most attractive options for generating crop cover maps because it enables computation of vegetation indices, which are useful for assessing the condition of vegetation. The Sentinel-2A Multispectral Instrument (MSI), which is a multispectral sensor with 13 bands covering the visible, near infrared and short-wave...

In this study, above-ground biomass (AGB) performance was evaluated by PALSAR-2 L-band and Landsat data for bamboo and mixed bamboo forest. The linear regression model was chosen and validated for forest biomass estimation in A Luoi district, Thua Thien Hue province, Vietnam. A Landsat 8 OLI image and a dual-polarized ALOS/PALSAR-2 L-band (HH, HV p...

Research Highlights: In this study, we classified natural forest into four forest types using time-series multi-source remotely sensed data through a proposed semi-supervised model developed and validated for mapping forest types and assessing forest transition in Vietnam. Background and Objectives: Data on current forest state and changes detectio...

In this study, various remote sensing data, modeling data and emission inventories were integrated to analyze the tempo-spatial distribution of biomass burning in mainland Southeast Asia and its effects on the local ambient air quality from 2001 to 2016. Land cover changes have been considered in dividing the biomass burning into four types: forest...

Remote sensing (RS)-based models play an important role in estimating and monitoring terrestrial ecosystem gross primary productivity (GPP). Several RS-based GPP models have been developed using different criteria, yet the sensitivities to environmental factors vary among models; thus, a comparison of model sensitivity is necessary for analyzing an...

Basal stem rot (BSR) disease caused by Ganoderma boninense is a major disease in oil palm plantations and there is no effective fungicide to control this disease. Several researchers have applied remote sensing for BSR studies, but, until now, WorldView-3 imagery has not been used to classify the severity of BSR disease symptoms. The objectives of...

In this study, we used ground-measured air pollutants and various remote sensing and meteorological datasets to explore the possible causes of the severe particulate matter (PM) pollution episodes of October and November 2015 in Northeast China. The three pollution episodes in different regions were elaborately characterized by analyzing the time v...

Leaf nutrients are needed for oil palm growth and production, and the nutrient contents of oil palm leaves can be determined by the chemical analyses of the number 9 and 17 leaves for young and adult palms, respectively. However, the accurate selection of the proper leaf for sampling is problematic. Remote sensing techniques based on the reflectanc...

We comprehensively analyzed the temporo-spatial changes in the CO2 concentrations in Australia from June 2009 to December 2016 using greenhouse gas monitoring satellites, Greenhouse Gases Observing Satellite (GOSAT) and Orbiting Carbon Observatory-2 (OCO-2). Regarding the spatial distribution, the CO2 concentration in central Australia was always h...

The identification and mapping of crops are important for estimating potential harvest as well as for agricultural field management. Optical remote sensing is one of the most attractive options because it offers vegetation indices and some data have been distributed free of charge. Especially, Sentinel-2A, which is equipped with a multispectral sen...

Developing techniques are required to generate agricultural land cover maps to monitor agricultural fields. Landsat 8 Operational Land Imager (OLI) offers reflectance data over the visible to shortwave-infrared range. OLI offers several advantages, such as adequate spatial and spectral resolution, and 16 day repeat coverage, furthermore, spectral i...

Quantitative estimations of the GPP (gross primary production) and its variations at spatial scales are important issues with future significance due to the increasing atmospheric CO 2 levels. However, the effects of the spa-tiotemporal variability in the atmospheric CO 2 concentrations on GPP estimations are challenging with respect to the terrest...

A crop classification method using satellite data is proposed as an alternative to the existing ground survey. In this study, crop types were classified using two kinds of SAR data (i.e., TerraSAR-X X-band dual-polarization data and Radarsat-2 C-band fully-polarization data) and Random Forests. Sigma naught polarimetric parameters were calculated f...

Crop classification maps are useful for estimating amounts of crops harvested, which could help address challenges in food security. Remote-sensing techniques are useful tools for generating crop maps. Optical remote sensing is one of the most attractive options because it offers vegetation indices (VIs) with frequent revisits and has adequate spat...

We used OCO-2 products and considered three factors that potentially affect CO2 concentration in Indonesia: sea surface temperature (SST), forest fires and vegetation. From 2014 to 2016, CO2 concentration in Indonesia showed a trend of increase, which is consistent with the global increase reported by the Greenhouse Gases Observing Satellite (GOSAT...

Sentinel-1A C-SAR and Sentinel-2A MultiSpectral Instrument (MSI) provide data applicable to the remote identification of crop type. In this study, six crop types (beans, beetroot, grass, maize, potato, and winter wheat) were identified using five C-SAR images and one MSI image acquired during the 2016 growing season. To assess the potential for acc...

In the summer of 2010, more than 6 hundred wildfires broke out in western Russia because of an unprecedented intense heat wave that resulted from strong atmospheric blocking. The present study evaluated the CO2 emissions using GOSAT (Greenhouse gases Observing SATellite) data from July 23 to August 18, 2010 for western Russia. The results demonstra...

Cloud and Aerosol Imager (CAI) onboard the Greenhouse Gases Observing Satellite (GOSAT) is a multi-band sensor designed to observe and acquire information on clouds and aerosols. In order to retrieve aerosol optical depth (AOD) over land from the CAI sensor, a Dark Target (DT) algorithm for GOSAT CAI was developed based on the strategy of the Moder...

Ganoderma boninense is a fungus that causes basal stem rot (BSR) disease in oil palm plantations. BSR is a major disease in oil palm plantations in both Indonesia and Malaysia. There is no effective treatment for curing BSR; current treatments only prolong the life of oil palms. One strategy to control BSR is early detection of G. boninense infecti...

This paper presents crop classification using satellite data to establish a mapping method to replace the existing ground survey. We used five scenes of C-band fully polarimetric SAR satellite Radarsat-2 data. Datasets of sigma naught and four polarimetric parameters, Freeman－Durden (FD), Van Zyl (VZ), Yamaguchi (YG), and Cloude－Pottier (CP), were...

In this paper, we introduced a new algorithm for retrieving aerosol optical depth (AOD) over land, from the Cloud and Aerosol Imager (CAI), which is one of the instruments on the Greenhouse Gases Observing Satellite (GOSAT) for detecting and correcting cloud and aerosol interference. We used the GOSAT and AErosol RObotic NETwork (AERONET) collocate...

In the past, oil palm density has been determined by manually counting trees every year in oil palm plantations. The measurement of density provides important data related to palm productivity, fertilizer needed, weed control costs in a circle around each tree, labourers needed, and needs for other activities. Manual counting requires many workers...

With China as the study area, MODIS MOD14A1 and MCD12Q1 products were used to derive daily crop residue burning spots from 2014 to 2015. After vectorization of crop residue burning pixels and with the use of fishnet, burning density distribution maps were eventually completed. Meanwhile, the daily air quality data from 150 cities in 2014 and 285 ci...

Rice is the second largest staple crop in the world and therefore plays an important role in food security. As a thermophilic crop, rice is sensitive to temperature changes. Thus, research on the chilling damage of rice is essential. The Sanjiang Plain is an emerging rice production area and is located at high latitudes in China, the world’s larges...

Agricultural residues are materials left over from the production of crops. The total amount of agricultural residues in China is about 660 million tons every year, while a large proportion of that is burnt directly on the croplands. Agricultural residues burning is a significant source of air pollution in developing countries including China. In t...

The Cloud and Aerosol Imager (CAI) is one of the subunits of observation instrument Thermal And Near-infrared Sensor for carbon Observation (TANSO) onboard the GOSAT, and is used to observe aerosol optical properties and clouds. TANSO-CAI includes 4 bands (370~390 nm, 668~688 nm, 860~880 nm and 1560~1680 nm), bands 1 to 3 have a 0.5-km spatial reso...

Carbon dioxide (CO2) is one of the most important greenhouse gases; its concentration and distribution have important implications on climate change. The El Ni?o Southern Oscillation (ENSO) is the Earth’s strongest climate fluctuation on inter-annual time scales and has global impacts. However, to date, there is no research on how ENSO affects the...

The Operational Land Imager (OLI) is the latest instrument in the Landsat series of satellite imagery, which officially began normal operations on May 30, 2013. The OLI includes two bands that are not on the Thematic Mapper (TM) series of sensors aboard Landsat-5 and 7; a cirrus band and a coastal/aerosol band. This paper compares the classificatio...

The classification maps are required for management and for the estimation of agricultural disaster compensation; however, those techniques have yet to be established. Some supervised learning models may allow accurate classification. In this study, the Random Forest (RF) classifier and the classification and regression tree (CART) were applied to...

Significant information about agricultural fields has been obtained through microwave remote sensing, and these techniques are increasingly being used to manage land and water resources for agricultural applications. Furthermore, synthetic aperture radar (SAR) systems are not dependent on atmospheric influences or weather conditions unlike passive...

Recently, some polarimetric decomposition techniques have been developed using multi-polarized synthetic aperture radar (SAR). In this study, the dual-polarized (HH/VV) SAR data acquired from TerraSAR-X were decomposed to three components using m-chi decomposition. Some models were developed using the double (even) bounce components and the crop he...

Classification maps are required for agricultural management and the estimation of agricultural disaster compensation. The extreme learning machine (ELM), a newly developed single hidden layer neural network is used as a supervised classifier for remote sensing classifications. In this study, the ELM was evaluated to examine its potential for multi...

Because of the limited number of observation stations and the short time series of orbiting carbon satellite data, it is difficult to monitor CO2 concentrations (XCO2) at broad spatial scales for long time spans. Therefore, we are limited in accurately forecasting change in XCO2. Studies based on the approach of using satellite sensor-derived data...

Crop classification maps are required for the management of crops and for the estimation of agricultural disaster compensation. In this study, classification using TerraSAR-X data (including TanDEM-X) was performed. Applying the m-chi decomposition to the dual-polarized SAR data (HH and VV polarization), the three components, double (even) bounce,...

This paper presents the results of monitoring the growth of crop vegetation using multi-temporal TerraSAR-X data. TerraSAR-X HH/VV images were collected in this study, and the temporal responses to the agricultural crops including beans, beet, maize and potato were analyzed using sigma nought. The crop height and canopy cover were measured during t...

This article describes the comparison of three different classification algorithms for mapping crops in Hokkaido, Japan, using TerraSAR-X data. In the study area, beans, beets, grasslands, maize, potatoes, and winter wheat were cultivated. Although classification maps are required for both management and estimation of agricultural disaster compensa...

Although classification maps are required for management and for the estimation of agricultural disaster compensation, those techniques have yet to be established. This paper describes the comparison of three different classification algorithms for mapping crops in Hokkaido, Japan, using TerraSAR-X (including TanDEM-X) dual-polarimetric data. In th...

This paper describes a method for monitoring winter wheat growth using multi-temporal TerraSAR-X dual-polarimetric data. Six TerraSAR-X HH/VV images were collected in Hokkaido, and the temporal responses to the winter wheat fields were analyzed. The height, moisture content and dry matter of the crops were measured at nearly the same time as TerraS...

Winter wheat is an important crop for many countries, and monitoring of its planted area is considered important. Optical sensors have been used to monitor agricultural land, and have shown good classification and monitoring capabilities. However, observations using optical sensors sometimes suffer from interference due to cloud cover or rain. In c...

This paper describes the classification of agricultural land use based on multi-temporal TerraSAR-X images taken during the vegetation season in Tokachi District, Hokkaido. Support Vector Machine (SVM) is becoming a popular alternative to traditional image classification methods because it performs accurate classifications using small training samp...

Aim of study: The ambrosia beetle, Platypus quercivorus, is a vector of Japanese oak wilt, which causes massive mortality of oak trees in Japan. ALOS/AVNIR-2 true color images can be used to help detect areas of oak wilt, although such detection by inventory surveys is not realistic. Applying pan-sharpening techniques, a higher spatial resolution m...

In this paper, an Urban Light Index (ULI) is constructed to facilitate analysis and quantitative evaluation of the process of urbanization and expansion rate by using DMSP/OLS Nighttime Light Data during the years from 1992 to 2010. A unit circle urbanization evaluation model is established to perform a comprehensive analysis of the urbanization pr...

The classification maps are required for the management and the estimation of agricultural disaster compensation; however, those techniques have yet to be established. Some supervised learning models may allow accurate classification. In this study, the Random Forest (RF) classifier and the classification and regression tree (CART) were applied to...

This paper presents the results of monitoring the growth of crop vegetation using multi-temporal TerraSAR-X data. TerraSAR-X HH/VV images were collected in this study, and the temporal responses to the agricultural crops including beans, beet, maize and potato were analyzed using sigma nought. The crop height and canopy cover were measured during t...

Surface roughness plays a considerable role on radar backscatter models designed for soil moisture estimation. Some parameters such as the root mean square height (s) and the correlation length (l) are used for evaluating surface roughness. Since each study uses a unique profile length, the relationships between radar signal and surface roughness p...

Soil moisture is important information for agricultural fields. Applying remote sensing techniques are useful for soil moisture estimation, while it is difficult to measure on a routine basis over large areas. Although the data acquired by Synthetic Aperture Radar (SAR) is sensitive for soil moisture, several factors, such as surface roughnessand v...

Wheat is an important crop for many countries, and monitoring of its planted area is viewed as an important issue. Optical sensors have been used for agricultural land use monitoring, and these have shown good classification and monitoring capabilities. However, the observations using optical sensors sometimes suffer from the interference of cloud...

This paper describes the long-term effects on vegetation following the catastrophic fire in 1987 on the northern Great Xing’an Mountain by analyzing the AVHRR GIMMS 15-day composite normalized difference vegetation index (NDVI) dataset. Both temporal and spatial characteristics were analyzed for natural regeneration and tree planting scenarios from...

Measurements of land-cover changes suggest that such shifts may alter atmospheric concentrations of greenhouse gases GHGs. However, owing to the lack of large-scale GHG data, a quantitative description of the relationships between land-cover changes and GHG concentrations does not exist on a regional scale. The Greenhouse Gases Observing Satellite...

Land degradation and global warming are currently highly active research topics. Land degradation can both change land cover and surface climate and significantly influence atmospheric circulation. Researches have verified that carbon dioxide (CO2) and methane (CH4) are major greenhouse gases (GHG) in the atmosphere and are directly affected by hum...

Carbon dioxide (CO(2)) is the most important greenhouse gas (GHG) in the atmosphere and is the greatest contributor to global warming. CO(2) concentration data are usually obtained from ground observation stations or from a small number of satellites. Because of the limited number of observations and the short time series of satellite data, it is d...

In Asia, sand dust storms (SDSs) occur nearly every year, especially in northern China. However, there is little research about the relationship between SDSs and greenhouse gases (GHGs). In this article, we selected four SDSs that occurred in Asia in the spring of 2009 and 2010. We monitored the areas covered by these SDSs using Moderate Resolution...

Post-fire vegetation can be monitored and analyzed over large areas in a time- and cost-effective manner by using satellite sensor imagery in combination with spatial analysis as provided by Geographical Information Systems (GIS). In this study, spatio-temporal distribution dynamics of burned area in the Northeast of China were analyzed by using a...

Developed by Japan, the Greenhouse Gases Observing Satellite (GOSAT), also known as IBUKI, was successfully launched on 23 January 2009 to monitor greenhouse gases on the Earth's surface. Observations started in April 2009, and data on Levels 1, 2 and 3 products became available to general users in November 2009, February 2010 and October 2010, res...

The Normalized Difference Vegetation Index (NDVI) has become one of the most widely used indices in remote sensing applications in a variety of fields. Many studies have compared the NDVI values for different satellite sensors. Nowadays, the Greenhouse Gases Observing Satellite (GOSAT) was successfully launched on January 23, 2009. It is used to mo...

The Intergovernmental Panel on Climate Change (IPCC) reported that humankind is causing global warming through the emission of greenhouse gases (GHG), particularly carbon dioxide (CO2) and methane (CH4). The global change will seriously impact human society and ecosystems, many factors have been identified that may reflect or cause variations in en...

The accuracy of a radiance transfer model neural network (RM-NN) for separating land surface temperature (LST) and emissivity from AST09 (the Advanced Spaceborne and Thermal Emission and Reflection Radiometer (ASTER) Standard Data Product, surface leaving radiance) is very high, but it is limited by the accuracy of the atmospheric correction. This...

This study uses a multiple linear regression method to composite standard Normalized Difference Vegetation Index (NDVI) time series (1982–2009) consisting of three kinds of satellite NDVI data (AVHRR, SPOT, and MODIS). This dataset was combined with climate data and land cover maps to analyze growing season (June to September) NDVI trends in northe...

The paper investigated the feasibility of Hyper spectra to determine the concentration of soil organic matter (SOM) in Harbin. The 95 soil samples were collected to a depth from 0 to 20 cm. Reflectance measurements from 350 nm to 2500 nm were collected in a controlled laboratory environment. Three multivariate techniques (stepwise multiple linear r...

From winter 2009 to spring 2010, due to decreasing precipitation and high temperature, Southwest China experienced the worst meteorological drought in 60 years. The drought has impacted large areas of Guizhou, Yunnan, Guangxi and Sichuan provinces. In this paper, climate data (precipitation and temperature) and SPOT VGT Normalized Difference Vegeta...

This paper explored the main driving forces and stresses contributing to the eco-environmental changes of Baishan City in Jilin Province, through the analysis of the ecological security problems in the City. The framework of DPSIR was applied to establish an ecological security assessment index system, and further, to create an ecological security...

In order to verify the feasibility of wetland cover information extraction for ALOS remote sensing image,classic inland freshwater wetland in Sanjiang Plain was taken as an example,spectral and textural characteristics of the image were analyzed,and classification characteristics of different cover types were discussed.Based on the methods of unsup...

The purpose of the paper is to study the measurement and estimation method of farmland in rural residential spots using SPOT5 remote sensing image on the platforms of ArcGIS and ERDAS and supplemented with GPS field sampling.Method is to combine 3S technologies with typical sampling.The results indicate that farmland area in the residential spots o...

Rapid urbanization as the result of population growth and economic development has been recognized as a critical process in urban area. It also affects the climatology of cities and their environment. This study have focused on map, compare, and analysis the land cover change during urbanization using ALOS and Landsat satellite data in two typical...

Net primary production (NPP) in the Yellow River Basin, China during 1982–1999 was estimated by the CASA model using the satellite data. When the estimated results are compared with other study, the similar results have been obtained. The yearly NPP (NPPT) has increasing tendency during 1982–1999 at the overall Yellow River Basin. The large mean an...

三江平原作为国家重要的农业生 产基地,长期以来自然生态环境尤其是大面积湿地受到大规模农业开发的强烈作用,生态环境发生了较大变化。本文以三江平原西北部富锦和同江市为例,应用RS 和GIS手段对研究区1975、1988、1993、1997、2001年和2006年6期Landsat遥感影像提取各地类面积,分析湿地农田化对该区 气候、水文、生物多样性等方面的影响,结果表明:30年来湿地减少51.38万公顷,耕地增加70.98万公顷,湿地农田化给该区域带来气候变暖、"冷 湿"效应减弱、生物多样性减少等不同程度的生态环境问题。根据统筹人与自然和谐的科学发展观,提出了恢复和重建三江平原湿地生态系统的对策和建议,研究该 地区湿地农田化具有重要意义,有利于促进经济、社会和生态环境可持续协调发展,保障国家商品粮...

An algorithm based on the radiance transfer model (MODTRAN4) and a dynamic learning neural network for estimation of near-surface air temperature from ASTER data are developed in this paper. MODTRAN4 is used to simulate radiance transfer from the ground with different combinations of land surface temperature, near surface air temperature, emissivit...

Four radiative transfer equations for Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) bands 11, 12, 13, and 14 are built involving six unknowns (average atmospheric temperature, land surface temperature, and four band emissivities), which is a typical ill-posed problem. The extra equations can be built by using linear or nonl...

Soil moisture is important information for agricultural fields in which erosion of upper soil layers depends upon the soil moisture and in which the yield depends on soil water contents during sowing, growing, and harvest periods. Although many studies have estimated moisture in bare soil fields using synthetic aperture radar (SAR) imaging, few mod...

A typical slope land with black soil in Guangrong small watershed of Northeast China was taken as the study area.Soil water content and bulk density were measured from soil samples.Spatial analysis,classic statistics,and geostatisitcs were used to explore the effects of topographic factors on soil water and bulk density.Results show that slope has...