[Grain yield estimation of wheat-maize rotation cultivated land based on Sentinel-2 multi-spectral image: A case study in Caoxian County, Shandong, China].

Establishing the remote sensing yield estimation model of wheat-maize rotation cultivated land can timely and accurately estimate the comprehensive grain yield. Taking the winter wheat-summer maize rotation cultivated land in Caoxian County, Shandong Province, as test object, using the Sentinel-2 images from 2018 to 2019, we compared the time-series feature classification based on QGIS platform and support vector machine algorithm to select the best method and extract sowing area of wheat-maize rotation cultivated land. Based on the correlation between wheat and maize vegetation index and the statistical yield, we screened the sensitive vegetation indices and their growth period, and obtained the vegetation index integral value of the sensitive spectral period by using the Newton-trapezoid integration method.

[Remote sensing inversion of cultivated land fertility at county scale based on SWCI-NDVI feature space].

It is objective needs during utilization and management of regional cultivated land resource to use remote sensing to accurately and efficiently retrieve the status of cultivated land fertility at county level and realize the gradation of cultivated land rapidly. In this study, with Dongping County as a case, using Landsat TM satellite imagery and cultivated land fertility evaluation data, the moisture vegetation fertility index (MVFI) was constructed based on surface water capacity index (SWCI) and normalized difference vegetation index (NDVI), and then the optimal inversion model was optimized to obtain the best inversion model, which was further applied and verified at the county scale. The results showed that the correlation coefficient between MVFI and integrated fertility index (IFI) was -0.

[Multi-scale spatial variability of soil salinity in typical fields of the Yellow River Delta in summer].

Soil salinization severely hinders the development of agricultural economy in the Yellow River Delta. Clarifying the spatial variability of soil salinity at multiple scales in the field is of great significance for the improvement and utilization of saline soils and agricultural production. In this study, by dividing the three dimensions of field, plot and ridge, we collceted 152 sets of conducti-vity data through field survey sampling in a summer maize field in Kenli County of the Yellow River delta.

Improving the Accuracy of the Hyperspectral Model for Apple Canopy Water Content Prediction using the Equidistant Sampling Method.

The influence of the equidistant sampling method was explored in a hyperspectral model for the accurate prediction of the water content of apple tree canopy. The relationship between spectral reflectance and water content was explored using the sample partition methods of equidistant sampling and random sampling, and a stepwise regression model of the apple canopy water content was established. The results showed that the random sampling model was Y = 0.

[Hyperspectral Estimation of Apple Tree Canopy LAI Based on SVM and RF Regression].

Leaf area index (LAI) is the dynamic index of crop population size. Hyperspectral technology can be used to estimate apple canopy LAI rapidly and nondestructively. It can be provide a reference for monitoring the tree growing and yield estimation.

[Soil Salinity Estimation Based on Near-Ground Multispectral Imagery in Typical Area of the Yellow River Delta].

This study chooses the core demonstration area of 'Bohai Barn' project as the study area, which is located in Wudi, Shandong Province. We first collected near-ground and multispectral images and surface soil salinity data using ADC portable multispectral camera and EC110 portable salinometer. Then three vegetation indices, namely NDVI, SAVI and GNDVI, were used to build 18 models respectively with the actual measured soil salinity.

[Land salinization information extraction method based on HSI hyperspectral and TM imagery].

This paper chose the typical salinization area in Kenli County of the Yellow River Delta as the study area, selected HJ-1A satellite HSI image at March 15, 2011 and TM image at March 22, 2011 as source of information, and pre-processed these data by image cropping, geometric correction and atmospheric correction. Spectral characteristics of main land use types including different degree of salinization lands, water and shoals were analyzed to find distinct bands for information extraction Land use information extraction model was built by adopting the quantitative and qualitative rules combining the spectral characteristics and the content of soil salinity. Land salinization information was extracted via image classification using decision tree method.

[Hyper spectral estimation method for soil alkali hydrolysable nitrogen content based on discrete wavelet transform and genetic algorithm in combining with partial least squares DWT-GA-PLS)].

Taking the Qihe County in Shandong Province of East China as the study area, soil samples were collected from the field, and based on the hyperspectral reflectance measurement of the soil samples and the transformation with the first deviation, the spectra were denoised and compressed by discrete wavelet transform (DWT), the variables for the soil alkali hydrolysable nitrogen quantitative estimation models were selected by genetic algorithms (GA), and the estimation models for the soil alkali hydrolysable nitrogen content were built by using partial least squares (PLS) regression. The discrete wavelet transform and genetic algorithm in combining with partial least squares (DWT-GA-PLS) could not only compress the spectrum variables and reduce the model variables, but also improve the quantitative estimation accuracy of soil alkali hydrolysable nitrogen content. Based on the 1-2 levels low frequency coefficients of discrete wavelet transform, and under the condition of large scale decrement of spectrum variables, the calibration models could achieve the higher or the same prediction accuracy as the soil full spectra.

[Satellite remote sensing retrieval of canopy nitrogen nutritional status of apple trees at blossom stage].

Taking Qixia City of Shandong, China as the study area, and based on the Landsat-5 TM and ALOS AVNIR-2 images, the canopy retrieval reflectance of apple trees at blossom stage was acquired. In combining with the measured reflectance of sample trees, the nitrogen-sensitive spectral indices were constructed and selected. By using the sensitive spectral indices as the independent variables, the nitrogen retrieval models were established, and the model with the best accuracy was used for spatial retrieve.

[Mapping environmental vulnerability from ETM + data in the Yellow River Mouth Area].

The environmental vulnerability retrieval is important to support continuing data. The spatial distribution of regional environmental vulnerability was got through remote sensing retrieval. In view of soil and vegetation, the environmental vulnerability evaluation index system was built, and the environmental vulnerability of sampling points was calculated by the AHP-fuzzy method, then the correlation between the sampling points environmental vulnerability and ETM + spectral reflectance ratio including some kinds of conversion data was analyzed to determine the sensitive spectral parameters.

[Hyperspectral estimation of kalium content in apple florescence canopy based on fuzzy recognition].

The objective of the present paper is fast and nondestructive estimate of kalium content using ASD FieldSpec3 spectrometer determined hyperspectral data in apple florescence canopy. According to detection of hyperspectral data of the apple florescence canopy and kalium content data at laboratory in Qixia city of experimental orchards in 2008 and 2009, the correlation analysis of hyperspectral reflectance and its eleven transforms with kalium content was proceeded. The biggest correlation coefficient as independent variable and the estimation model of kalium content were established based on fuzzy recognition algorithms.

[Remote sensing techniques of apple orchard information extraction based on linear spectral unmixing with measured data].

Taking Qixia City, Shandong Province of China as the research region, and by using pixel unmixing for the TM image at apple flowering stage, the apple orchard information was extracted. Based on the measured spectral end-members, wavelet transform was adopted to improve the linear unmixing model. The improved linear spectral unmixing model, measured end-member based linear spectral unmixing model, and TM image end-member based linear spectral unmixing model were employed to extract the apple orchard information, and the ALOS data were used for accuracy estimation.

[Quantitative remote sensing retrieval of apple tree canopy reflectance at blossom stage in hilly area].

By using the TM and ALOS images with different resolutions at the prosperous blossom stage of apple trees in Qixia City of Shandong Province, and taking the slope aspect coefficient and the ratio of canopy flower to leaf into account, the ground surface reflectance was retrieved through radiometric correction. The canopy reflectance of the apple trees was further retrieved by pixel unmixing method, and the retrieval effect and accuracy were assessed by the comparison of the retrieved reflectance with the measured canopy reflectance and apparent reflectance of 30 sample apple orchards. The results showed that radiometric correction effectively weakened the effects of atmosphere and topography, recovered the ground objects in the shadows, and obviously enhanced the analytical ability of ground surface retrieval reflectance images.

[Hyperspectral estimation models of chlorophyll content in apple leaves].

The present study chose the apple orchard of Shandong Agricultural University as the study area to explore the method of apple leaf chlorophyll content estimation by hyperspectral analysis technology. Through analyzing the characteristics of apple leaves' hyperspectral curve, transforming the original spectral into first derivative, red edge position and leaf chlorophyll index (LCI) respectively, and making the correlation analysis and regression analysis of these variables with the chlorophyll content to establish the estimation models and test to select the high fitting precision models. Results showed that the fitting precision of the estimation model with variable of LCI and the estimation model with variable of the first derivative in the band of 521 and 523 nm was the highest.

[Spatial distribution of wintering Engraulis japonicus and its relationship with the inter-annual variations of water temperature in central and southern Yellow Sea].

Abstract: This paper studied the inter-annual variations in the spatial distribution of wintering anchovy (Engraulis japonicus) in central and southern Yellow Sea, based on the 1986-2010 bottom trawl survey data and related sea surface temperature (SST) data obtained by remote sensing, and approached the relationships between the inter-annual variations in the spatial distribution of the wintering anchovy and the SST, by using GIS technique, spatial analysis and correlation analysis. In 1986-2010, the wintering anchovy in the study area had apparent inter-annual variations in spatial distribution, with its abundance dropped to the lowest level and its distribution moved shoreward in 2004, and the abundance rebounded and centralized in the eastern waters in 2010. The centralized distribution regions of the anchovy's capture locations and stock density in longitudinal and latitudinal directions also had apparent inter-annual variations.

[Hyper-spectral estimation of soil organic matter content based on wavelet transformation].

A total of 60 soil samples with approximate contents of N, P, and K and greatly different content of organic matter were selected by statistical analysis. Through hyper-spectral detection and analysis, the first derivative spectrum of the soil logarithmic reflectance was obtained, and was decomposed by the Bior 1.3 wavelet function.

[Quantitative models between canopy hyperspectrum and its component features at apple tree prosperous fruit stage].

Hyperspectral technique has become the basis of quantitative remote sensing. Hyperspectrum of apple tree canopy at prosperous fruit stage consists of the complex information of fruits, leaves, stocks, soil and reflecting films, which was mostly affected by component features of canopy at this stage. First, the hyperspectrum of 18 sample apple trees with reflecting films was compared with that of 44 trees without reflecting films.

[Standardization of technical methods for apple fluorescence canopy spectral detection].

Aiming at spectral detection of apple fluorescence canopy, the present paper carried out spectral detection tests under different weather conditions, different detection times, and different detection heights and angles to apple canopy in the two years of 2008 and 2009, so as to analyze impacts of these factors on apple canopy spectral characteristics and explore standardized spectral detection methods for apple fluorescence canopy. The results indicated the regularity in spectral reflectance of apple fluorescence canopy to a certain degree under different conditions, especially in the 760-1 350 nm near-infrared bands. The authors found that canopy spectral reflectance declined along with the decrease in sunshine and it is appropriate to detect canopy spectrum in sunny days with few clouds.

[Hyperspectrum based prediction model for nitrogen content of apple flowers].

The present paper aims to quantitatively retrieve nitrogen content in apple flowers, so as to provide an important basis for apple informationization management. By using ASD FieldSpec 3 field spectrometer, hyperspectral reflectivity of 120 apple flower samples in full-bloom stage was measured and their nitrogen contents were analyzed. Based on the apple flower original spectrum and first derivative spectral characteristics, correlation analysis was carried out between apple flowers original spectrum and first derivative spectrum reflectivity and nitrogen contents, so as to determine the sensitive bands.

[Monitoring models for phosphorus content of apple flowers based on hyperspectrum].

By using ASD FieldSpec 3 field spectrometer, the hyperspectral reflectance of apple flowers at full-blooming stage was measured under laboratory conditions, and the correlations of the hyperspectral reflectance with the phosphorus content of apple flowers were analyzed based on the original spectrum and the first derivative spectral characteristics of the flowers. The sensitive wavebands were determined, the characteristic spectral parameters were constructed, and the monitoring models for the phosphorus content of apple flowers were established accordingly. Correlation analysis showed that the phosphorus content of apple flowers was significantly positively correlated with the original spectral reflectance at 350-370 nm, 670-1385 nm, and 1620-1760 nm, and the first derivative reflectance at 500-520 nm, and significantly negatively correlated with the first derivative reflectance at 670-730 nm.

[Study on hyperspectral characteristics of apple florescence canopy].

The present study aims to systematically analyze the hyperspectral characteristics of apple florescence canopy and explore the sensitive spectra to provide the theoretical basis for large area apple information extracting and remote sensing retrieval for nutrition diagnosis. Based on the 120 hyperspectral data of apple florescence canopy acquired with ASD Field Spec 3 portable object spectrometer, the effects of different sample numbers on hyperspectral characteristics were analyzed. Using variance analysis method, the hyperspectral characteristics of apple florescence canopy and the sensitive wave bands were obtained.

[Spatiotemporal variation of eco-environmental frangibility based on remote sensing and catastrophe theory: a case study of Kenli County in Yellow River Delta, China].

Based on remote sensing and the nonlinear theories of entropy and catastrophe, the spatiotemporal variation of eco-environmental frangibility in Kenli County of Yellow River Delta was analyzed through the installation of sampling plots. The methods of analyzing and estimating eco-environmental frangibility were also established. The results indicated that in 1987-2005, the environment of Kenli County tended to deteriorating, and two catastrophes of environmental frangibility occurred, one in 1997, and the other in 2004.