Heng Dong

Simple method to determine the Priestley-Taylor parameter for evapotranspiration estimation using Albedo-VI triangular space from MODIS data

In this contribution, we present a simple method based on Albedo-VI (vegetation index) triangular space to determine the Priestley–Taylor parameter for estimating evaporative fraction (EF) and evapotranspiration (ET) in arid and semi-arid regions. We apply this method to MODIS and observation data acquired during the Heihe river basin field experiment from July 1 to September 30, 2008. Results show that the decreasing trend of the estimated EF from MODIS data is consistent with that of precipitation during the period of day 183 to 274, 2008. The bias of estimated daily ET deviating from the corresponding ground-measured ET is −8.66 W/m2 and the root-mean-square error is 21.55 W/m2, indicating the Albedo-VI triangular method has a potential in ET estimation as a simple satellite-based method independent of surface ancillary data.

Modified Shortwave Infrared Perpendicular Water Stress Index: A Farmland Water Stress Monitoring Method

AbstractCrop water stress monitoring by remote sensing has been the focus of numerous studies. In this paper, specifically red (630–690 nm) and shortwave infrared (SWIR; 1550–1750 nm) wavelength bands are identified to monitor farmland water stress, and a method [modified shortwave infrared perpendicular water stress index (MSPSI)] is developed that is based on the spectral space constructed by SWIR − Red (Rd) and SWIR + Red (Rs). The MSPSI stayed at mostly the same water stress level for full vegetation coverage cases with high vegetation water content and saturated bare soil as well as full vegetation coverage with extremely low vegetation water and dry bare soil in the Rs–Rd spectral feature space. This approach makes the water stress conditions between different covers comparable and the MSPSI applicable to farmland water stress monitoring in different vegetation covers throughout the growing season. To validate the proposed index, the MSPSI calculated from Thematic Mapper images and Moderate Resoluti...

The development of a new model on vegetation water content

Remote sensing monitoring and inversion research of vegetation water content is one of the most important developments of quantitative remote sensing theory and application. The common features of spectral reflectance from vegetation foliage upon leaf dehydration are decreasing water absorption in the near-infrared (NIR) and short-wave-infrared (SWIR). We studied that leaf water indexes in the NIR and SWIR were the most suitable for the assessment of leaf water content and developed a new model TWI (triangle vegetation water index) to estimate both canopy and single leaf water content. From the results of validation perspective, this model has better estimation accuracy at both canopy and single leaf water content comparing to WI, PWI, and NDWI. Validation was established on the basis of PROSPECT+SAIL estimation and ground measured data. So the model had good reliability and great potential to monitor vegetation water content.

Hyperspectral vegetation indices for crop chlorophyll estimation: Assessment, modeling and validation

This study summarizes 12 spectral indices for chlorophyll inversion, including traditional multi-spectral indices and newly published indices constructed based on “Red Edge” (680-750nm) and “Double-Peak” in red edge region. Among them, some are good candidates to resist Leaf Area Index (LAI) variations, but some are not. By using forward model simulations and in-situ measurements data, we systematically tested these indices and picked out the best one which (1) has the highest sensitivity to chlorophyll; (2) has the best resistance to LAI variation. Then predictive equations were developed from simulated data and validated using winter wheat ground measurement data collected in 2011, Yucheng Station at Chinese Academy of Sciences.

The component-based design and development of remote sensing system for drought monitoring

In the field of drought monitoring using remote sensing, the software has been lagging behind the applications. For the operational needs of monitoring and evaluating drought, a professional remote sensing application system (named RSDMS) is designed and developed with the concept of component-based technology. Starting from the architecture design, this article details the component-based design patterns of this system, and then discusses some key techniques during the development process. After achieving the general-purpose functionalities, this system also integrates a variety of drought monitoring models in the form of component, showing great flexibility. Meanwhile, the results of preliminary application in Ningxia region of northwestern China are presented to indicate that the system has a good practice effect.

The variation analysis of land surface albedo in Beijing in recent ten years

The surface land albedo is an important parameter of the energy balance. It is very significant for the urban micro-climate and environment to research the variation and analysis of land surface albedo. In this paper, the variation of land surface albedo in Beijing in recent ten years, the correlation of the albedo and underlying surface type, the correlation of the albedo and LST and NDVI were studied based on ETM+ data in 2010 and 1999. The conclusions of the paper are as followed: (1) The average albedo of second, third, fourth and fifth ring in Beijing were gradually increased. The albedo of Beijing area in 2010 reduced 0.0075 compared with 1999; the albedo of main city area within fifth ring road reduced 0.0108; the albedo of the area between third ring road and fourth ring was the biggest drop range area, and it reduced 0.0135; the albedo of the area without fifth ring was the smallest range area, it reduced 0.0048. (2) The average albedo of land cover types in order from high to low: new construction areas, farmland, bare land, woodland, villages, construction zone, paddy fields, water. The change of land surface type led to the albedo difference in Beijing between 2010 and 1999.

Validation of GLASS albedo products using ground measurements and landsat TM data

The purpose of this paper is to assess the quality of the Global Land Surface Satellite (GLASS) albedo products, which are being generated in China under the 863 key project entitled “Generation and Applications of Global Products of Essential Land Variables”. Ground measurements at twelve sites over three land cover types were collected from AmeriFlux and used to calibrate and validate the albedo products derived from Landsat TM images, and then the validated TM albedo products were aggregated to 1 km resolution to evaluate the accuracy of GLASS albedo products. The validation results demonstrated that GLASS albedo products have a high accuracy, with an overall root mean square error (RMSE) of 0.026 and bias of -0.009. In order to better understand the accuracy of GLASS albedo products, further validations need to be performed over more land cover types and at more ground sites.

Study on quantitative retrieval of soil nutrients

Soil spectral reflectance is affected by soil physicochemical characteristics and the physical basis of the soil remote sensing. Generally, the impact factors of the soil spectral features include water content, organic matter content, iron oxides content, physical composition and the parent material. In this study, a portable ASD FieldSpec Pro FR was used to collect the spectra of soil samples. The sensitive bands were selected by analyzing the relationship between nutrients and soil spectral features. Then the inversion models of soil nitrogen and organic were established by linear regression separately. The result showed that the content of soil nitrogen and soil organic can be well retrieved from remote sensing.

Validation for the absolute radiometric calibration of the HJ-1B CCD sensors of China

On September 6, 2008, the satellite HJ-1B was launched into a sun-synchronous, near-polar orbit. In order to determine temporal changes of the absolute radiometric calibration of the HJ-1B satellite in flight, a program was carried out at DunHuang calibration field, Gansu province of China, from August 19 to 30, 2009. In this work, reflectance -based calibration method was employed to simulate the absolute calibration coefficients of the HJ-1B CCD sensors. Then the cotton field, cement court, water pool and test site was selected to validate the calibration coefficient. The validation results indicated that there had a good agreement between the imaged-based reflectance and the ground measurement of the type of cement court and test site. On the other hand, there had a disagreement of the type of cotton field and water because of the effect of mixed pixel.

A component-based system for agricultural drought monitoring by remote sensing

In recent decades, various kinds of remote sensing-based drought indexes have been proposed and widely used in the field of drought monitoring. However, the drought-related software and platform development lag behind the theoretical research. The current drought monitoring systems focus mainly on information management and publishing, and cannot implement professional drought monitoring or parameter inversion modelling, especially the models based on multi-dimensional feature space. In view of the above problems, this paper aims at fixing this gap with a component-based system named RSDMS to facilitate the application of drought monitoring by remote sensing. The system is designed and developed based on Component Object Model (COM) to ensure the flexibility and extendibility of modules. RSDMS realizes general image-related functions such as data management, image display, spatial reference management, image processing and analysis, and further provides drought monitoring and evaluation functions based on internal and external models. Finally, China’s Ningxia region is selected as the study area to validate the performance of RSDMS. The experimental results show that RSDMS provide an efficient and scalable support to agricultural drought monitoring.