As a kind of soil-borne epidemic disease, bacterial wilt (BW) is one of the most serious diseases... more As a kind of soil-borne epidemic disease, bacterial wilt (BW) is one of the most serious diseases in tomatoes in southern China, which may significantly reduce food quality and the total amount of yield. Hyperspectral remote sensing can detect crop diseases in the early stages and offers potential for BW detection in tomatoes. Tomatoes in southern China are commonly cultivated in greenhouses or bird nets, limiting the application of remote sensing based on natural sunlight. To resolve these issues, we collected the spectrum of tomatoes firstly using the HS-VN1000B Portable Intelligent Spectrometer, which is equipped with a simulated solar light source. We then proposed a tomato BW detection model based on some optimal spectral features. Specifically, these optimal features, including vegetation indexes and principal components (PCs), were extracted by the sequential forward selection (SFS), the simulated annealing (SA), and the genetic algorithm (GA) and were finally fed into the su...
The effective integration of aerial remote sensing data and ground multi-source data has always b... more The effective integration of aerial remote sensing data and ground multi-source data has always been one of the difficulties of quantitative remote sensing. A new monitoring mode is designed which installs the hyperspectral imager on the UAV and places a buoy spectrometer on the river. Water samples are collected simultaneously to obtain in situ assay data of total phosphorus, total nitrogen, COD, turbidity and chlorophyll during data collection. The cross correlogram spectral matching (CCSM) algorithm is used to match the data of the buoy spectrometer with the UAV spectral data to reduce the UAV data noise significantly. An absorption characteristics recognition algorithm (ACR) is designed to realize a new method for comparing UAV data with laboratory data. This method takes into account the spectral characteristics and the correlation characteristics of test data synchronously. It is concluded that the most accurate water quality parameters can be calculated by using the regressio...
Monitoring the spatio-temporal dynamics of the Eastern Plain Lake (EPL) is vital to the local env... more Monitoring the spatio-temporal dynamics of the Eastern Plain Lake (EPL) is vital to the local environment and economy. However, due to the limitations and efficiency of traditional image formats in storing and processing large amounts of images and optimal threshold adjustments are often necessary for water/non-water separation based on traditional multi-band/spectral water indexes over large areas and in the long-term, previous studies have either been on a short period or mainly focused on water inundation dynamics of several lakes. To address these issues, a multi-dimensional dataset (MDD) storage format was used to efficiently organize more than ~7000 time series composite MODIS images. Furthermore, a universal normalized water index (UNWI) was developed based on full-spectrum information to simplify optimal threshold adjustments. Consequently, the present study analyzed the patterns of spatio-temporal water dynamic patterns and potential driving factors of inundation changes at...
Large-scale crop mapping is essential for agricultural management. Phenological variation often e... more Large-scale crop mapping is essential for agricultural management. Phenological variation often exists in the same crop due to different climatic regions or practice management, resulting in current classification models requiring sufficient training samples from different regions. However, the cost of sample collection is more time-consuming, costly, and labor-intensive, so it is necessary to develop automatic crop mapping models that require only a few samples and can be extended to a large area. In this study, a new white bolls index (WBI) based on the unique canopy of cotton at the bolls opening stage was proposed, which can characterize the intensity of bolls opening. The value of WBI will increase as the opening of the bolls increases. As a result, the white bolls index can be used to detect cotton automatically from other crops. Four study areas in different regions were used to evaluate the WBI performance. The overall accuracy (OA) for the four study sites was more than 82%...
2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2013
Estimating Chlorophyll-a concentration from the inland turbid water has been an important researc... more Estimating Chlorophyll-a concentration from the inland turbid water has been an important research issue for preserving and managing the ecological issues related to the lives of both flora and fauna. Hyperspectral remote sensing is being exploited to retrieve the true estimation of phytoplankton from all platforms like satellite, airborne sensors and handheld field spectroradiometers. This study was aimed to utilize both satellite sensors and field spectrometers for proper assessment of Chlorophyll-a. 4-band model with band combination [Rrs(λ<inf>1</inf>)<sup>−1</sup> − Rrs(λ<inf>2</inf>)<sup>−1</sup>] × [Rrs(λ<inf>4</inf>)<sup>−1</sup> − Rrs(λ<inf>3</inf>)<sup>−1</sup>]<sup>−1</sup> is found better than other models, while for Landsat ETM+, band combination b1/b2 is found better for estimating Chlorophyll-a as compared to other band combinations. It is also found that FLAASH...
ABSTRACT: Crop classification plays an important role in effective and controllable agricultural ... more ABSTRACT: Crop classification plays an important role in effective and controllable agricultural management. In this paper, nine scenes of Landsat8_OLI data in 2013 were collected for cotton planting area extraction in Shawan country of Xinjiang Uygur Autonomous Region, China. Normalized Difference Vegetation Index (NDVI) time series were generated to characterize the phenological pattern of each crop type. The optimal temporal reflectance image was chosen by analyzing the difference of NDVI profile between cotton and other crop types. The hierarchical classification strategy was performed on the three features of NDVI time series, NDVI statistics and reflectance. Firstly a simple decision tree was built on NDVI statistics and reflectance to extract vegetation cover; then various types of crops were distinguished by support vector machine (SVM) and maximum likelihood supervised classifier (MLC), thereby cotton plating area was extracted. A comprehensive evaluation for the cotton ext...
Journal of the Indian Society of Remote Sensing, 2021
Study the response mechanism of Canopy spectral reflectance (CSR) to cotton nitrogen fertilizer, ... more Study the response mechanism of Canopy spectral reflectance (CSR) to cotton nitrogen fertilizer, propose the sensitive band and center wavelength of cotton leaf nitrogen content (LNC), and compare the response characteristics of various vegetation indexes to LNC, propose a vegetation index that responds well to LNC and construct estimating model. This experiment sets five nitrogen fertilizer levels, namely N0 (control), N120 (120 kg/hm2), N240 (240 kg/hm2), N360 (360 kg/hm2), N480 (480 kg/hm2). Among them, referring to the conventional nitrogen fertilizer is applied by local farmers (N330, 330 kg/hm2). The results showed the following: (1) Visible light and near-infrared (NIR) can be used as two large ranges for precise monitoring of nitrogen, especially the CSR in the NIR range differs significantly under different nitrogen fertilizers. In the early stage of cotton growth, the CSR decreased with the nitrogen application rate increase, in a suitable nitrogen environment (360 kg/hm2)...
Accurate and timely information on the spatial distribution of crops is of great significance to ... more Accurate and timely information on the spatial distribution of crops is of great significance to precision agriculture and food security. Many cropland mapping methods using satellite image time series are based on expert knowledge to extract phenological features to identify crops. It is still a challenge to automatically obtain meaningful features from time-series data for crop classification. In this study, we developed an automated method based on satellite image time series to map the spatial distribution of three major crops including maize, rice, and soybean in northeastern China. The core method used is the nonlinear dimensionality reduction technique. However, the existing nonlinear dimensionality reduction technique cannot handle missing data, and it is not designed for subsequent classification tasks. Therefore, the nonlinear dimensionality reduction algorithm Landmark–Isometric feature mapping (L–ISOMAP) is improved. The advantage of the improved L–ISOMAP is that it does...
Land cover data is crucial for earth system modelling, natural resources management, and conserva... more Land cover data is crucial for earth system modelling, natural resources management, and conservation planning. Remotely sensed time-series data capture dynamic behavior of vegetation, and have been widely used for land cover mapping. Temporal profiles of vegetation index (VI), especially normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI), are the most used features derived from time-series spectral data. Whether NDVI or EVI is optimal to generate temporal profiles has not been evaluated. The universal normalized vegetation index (UNVI), a relatively new index with all spectral bands incorporated, has been proved to be more effective than several commonly used satellite-derived VIs in some application scenarios. In this study, we explored the ability of UNVI time series for discriminating different vegetation types in Chaoyang prefecture, northeast China, in comparison with normalized NDVI, EVI, triangle vegetation index (TVI), and tasseled cap transfo...
Remote sensing (RS) provides operational monitoring of terrestrial vegetation. For optical RS, ve... more Remote sensing (RS) provides operational monitoring of terrestrial vegetation. For optical RS, vegetation information is generally derived from surface reflectance (ρ). More generally, vegetation indices (VIs) are built on the basis of ρ as proxies for vegetation traits. At canopy level, ρ can be affected by a variety of factors, including leaf constituents, canopy structure, background reflectivity, and sun-sensor geometry. Consequently, VIs are mixtures of different information. In this study, a global sensitivity analysis (GSA) is made for several commonly used satellite-derived VIs in order to better understand the application of these VIs at large scales. The sensitivities of VIs to different parameters are analyzed on the basis of PROSPECT-SAIL (PROSAIL) radiative transfer model simulations, which apply for homogeneous canopies, and random forest (RF) learning. Specifically, combined factors such as canopy chlorophyll content (CCC) and canopy water content (CWC) are introduced...
ABSTRACT Refractivity happens due to stratification in the lower boundary layer over oceans due t... more ABSTRACT Refractivity happens due to stratification in the lower boundary layer over oceans due to variability of moisture, temperature, wind and sea surface temperature which collectively may lead to generate evaporation duct. The evaporation duct has a significant impact on the spread of electromagnetic waves in the atmosphere over oceans both from the meteorological and military point of view. This ducting sometimes supports normal propagation of radar signals and sometimes may cause distortion and attenuation of signals depending on the height of evaporation duct. This leads to over-estimation and under-estimation of rainfall by weather radar meteorologically and for other targets militarily. The aim of this study was not only to locate evaporation duct height but also to check the efficiency of Weather Research and Forecasting Model (WRF) and Babin’s model so that results may be used in applying correction measures for precise identification of targets by radar. In this study by utilizing the high vertical resolution of WRF for the simulation of different meteorological parameters, the Babin’s method was used for calculating the evaporation duct height over South China Sea for the two months, April and July. Very clear duct heights were calculated at different areas over sea in different time domains. Study reveals that maximum height existed in the month of April although July was rich with different EDHs in different regions in contrast to April. It was found that in most of the cases EDH was higher or maximum when relative humidity was comparatively lower and air temperature and wind speed were comparatively higher. This study paves a way for futuristic study of evaporation duct monitoring and forecasting by assimilation of remote sensing data especially through that of Geostationary satellites by incorporating verification measures from radar
As a kind of soil-borne epidemic disease, bacterial wilt (BW) is one of the most serious diseases... more As a kind of soil-borne epidemic disease, bacterial wilt (BW) is one of the most serious diseases in tomatoes in southern China, which may significantly reduce food quality and the total amount of yield. Hyperspectral remote sensing can detect crop diseases in the early stages and offers potential for BW detection in tomatoes. Tomatoes in southern China are commonly cultivated in greenhouses or bird nets, limiting the application of remote sensing based on natural sunlight. To resolve these issues, we collected the spectrum of tomatoes firstly using the HS-VN1000B Portable Intelligent Spectrometer, which is equipped with a simulated solar light source. We then proposed a tomato BW detection model based on some optimal spectral features. Specifically, these optimal features, including vegetation indexes and principal components (PCs), were extracted by the sequential forward selection (SFS), the simulated annealing (SA), and the genetic algorithm (GA) and were finally fed into the su...
The effective integration of aerial remote sensing data and ground multi-source data has always b... more The effective integration of aerial remote sensing data and ground multi-source data has always been one of the difficulties of quantitative remote sensing. A new monitoring mode is designed which installs the hyperspectral imager on the UAV and places a buoy spectrometer on the river. Water samples are collected simultaneously to obtain in situ assay data of total phosphorus, total nitrogen, COD, turbidity and chlorophyll during data collection. The cross correlogram spectral matching (CCSM) algorithm is used to match the data of the buoy spectrometer with the UAV spectral data to reduce the UAV data noise significantly. An absorption characteristics recognition algorithm (ACR) is designed to realize a new method for comparing UAV data with laboratory data. This method takes into account the spectral characteristics and the correlation characteristics of test data synchronously. It is concluded that the most accurate water quality parameters can be calculated by using the regressio...
Monitoring the spatio-temporal dynamics of the Eastern Plain Lake (EPL) is vital to the local env... more Monitoring the spatio-temporal dynamics of the Eastern Plain Lake (EPL) is vital to the local environment and economy. However, due to the limitations and efficiency of traditional image formats in storing and processing large amounts of images and optimal threshold adjustments are often necessary for water/non-water separation based on traditional multi-band/spectral water indexes over large areas and in the long-term, previous studies have either been on a short period or mainly focused on water inundation dynamics of several lakes. To address these issues, a multi-dimensional dataset (MDD) storage format was used to efficiently organize more than ~7000 time series composite MODIS images. Furthermore, a universal normalized water index (UNWI) was developed based on full-spectrum information to simplify optimal threshold adjustments. Consequently, the present study analyzed the patterns of spatio-temporal water dynamic patterns and potential driving factors of inundation changes at...
Large-scale crop mapping is essential for agricultural management. Phenological variation often e... more Large-scale crop mapping is essential for agricultural management. Phenological variation often exists in the same crop due to different climatic regions or practice management, resulting in current classification models requiring sufficient training samples from different regions. However, the cost of sample collection is more time-consuming, costly, and labor-intensive, so it is necessary to develop automatic crop mapping models that require only a few samples and can be extended to a large area. In this study, a new white bolls index (WBI) based on the unique canopy of cotton at the bolls opening stage was proposed, which can characterize the intensity of bolls opening. The value of WBI will increase as the opening of the bolls increases. As a result, the white bolls index can be used to detect cotton automatically from other crops. Four study areas in different regions were used to evaluate the WBI performance. The overall accuracy (OA) for the four study sites was more than 82%...
2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2013
Estimating Chlorophyll-a concentration from the inland turbid water has been an important researc... more Estimating Chlorophyll-a concentration from the inland turbid water has been an important research issue for preserving and managing the ecological issues related to the lives of both flora and fauna. Hyperspectral remote sensing is being exploited to retrieve the true estimation of phytoplankton from all platforms like satellite, airborne sensors and handheld field spectroradiometers. This study was aimed to utilize both satellite sensors and field spectrometers for proper assessment of Chlorophyll-a. 4-band model with band combination [Rrs(λ<inf>1</inf>)<sup>−1</sup> − Rrs(λ<inf>2</inf>)<sup>−1</sup>] × [Rrs(λ<inf>4</inf>)<sup>−1</sup> − Rrs(λ<inf>3</inf>)<sup>−1</sup>]<sup>−1</sup> is found better than other models, while for Landsat ETM+, band combination b1/b2 is found better for estimating Chlorophyll-a as compared to other band combinations. It is also found that FLAASH...
ABSTRACT: Crop classification plays an important role in effective and controllable agricultural ... more ABSTRACT: Crop classification plays an important role in effective and controllable agricultural management. In this paper, nine scenes of Landsat8_OLI data in 2013 were collected for cotton planting area extraction in Shawan country of Xinjiang Uygur Autonomous Region, China. Normalized Difference Vegetation Index (NDVI) time series were generated to characterize the phenological pattern of each crop type. The optimal temporal reflectance image was chosen by analyzing the difference of NDVI profile between cotton and other crop types. The hierarchical classification strategy was performed on the three features of NDVI time series, NDVI statistics and reflectance. Firstly a simple decision tree was built on NDVI statistics and reflectance to extract vegetation cover; then various types of crops were distinguished by support vector machine (SVM) and maximum likelihood supervised classifier (MLC), thereby cotton plating area was extracted. A comprehensive evaluation for the cotton ext...
Journal of the Indian Society of Remote Sensing, 2021
Study the response mechanism of Canopy spectral reflectance (CSR) to cotton nitrogen fertilizer, ... more Study the response mechanism of Canopy spectral reflectance (CSR) to cotton nitrogen fertilizer, propose the sensitive band and center wavelength of cotton leaf nitrogen content (LNC), and compare the response characteristics of various vegetation indexes to LNC, propose a vegetation index that responds well to LNC and construct estimating model. This experiment sets five nitrogen fertilizer levels, namely N0 (control), N120 (120 kg/hm2), N240 (240 kg/hm2), N360 (360 kg/hm2), N480 (480 kg/hm2). Among them, referring to the conventional nitrogen fertilizer is applied by local farmers (N330, 330 kg/hm2). The results showed the following: (1) Visible light and near-infrared (NIR) can be used as two large ranges for precise monitoring of nitrogen, especially the CSR in the NIR range differs significantly under different nitrogen fertilizers. In the early stage of cotton growth, the CSR decreased with the nitrogen application rate increase, in a suitable nitrogen environment (360 kg/hm2)...
Accurate and timely information on the spatial distribution of crops is of great significance to ... more Accurate and timely information on the spatial distribution of crops is of great significance to precision agriculture and food security. Many cropland mapping methods using satellite image time series are based on expert knowledge to extract phenological features to identify crops. It is still a challenge to automatically obtain meaningful features from time-series data for crop classification. In this study, we developed an automated method based on satellite image time series to map the spatial distribution of three major crops including maize, rice, and soybean in northeastern China. The core method used is the nonlinear dimensionality reduction technique. However, the existing nonlinear dimensionality reduction technique cannot handle missing data, and it is not designed for subsequent classification tasks. Therefore, the nonlinear dimensionality reduction algorithm Landmark–Isometric feature mapping (L–ISOMAP) is improved. The advantage of the improved L–ISOMAP is that it does...
Land cover data is crucial for earth system modelling, natural resources management, and conserva... more Land cover data is crucial for earth system modelling, natural resources management, and conservation planning. Remotely sensed time-series data capture dynamic behavior of vegetation, and have been widely used for land cover mapping. Temporal profiles of vegetation index (VI), especially normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI), are the most used features derived from time-series spectral data. Whether NDVI or EVI is optimal to generate temporal profiles has not been evaluated. The universal normalized vegetation index (UNVI), a relatively new index with all spectral bands incorporated, has been proved to be more effective than several commonly used satellite-derived VIs in some application scenarios. In this study, we explored the ability of UNVI time series for discriminating different vegetation types in Chaoyang prefecture, northeast China, in comparison with normalized NDVI, EVI, triangle vegetation index (TVI), and tasseled cap transfo...
Remote sensing (RS) provides operational monitoring of terrestrial vegetation. For optical RS, ve... more Remote sensing (RS) provides operational monitoring of terrestrial vegetation. For optical RS, vegetation information is generally derived from surface reflectance (ρ). More generally, vegetation indices (VIs) are built on the basis of ρ as proxies for vegetation traits. At canopy level, ρ can be affected by a variety of factors, including leaf constituents, canopy structure, background reflectivity, and sun-sensor geometry. Consequently, VIs are mixtures of different information. In this study, a global sensitivity analysis (GSA) is made for several commonly used satellite-derived VIs in order to better understand the application of these VIs at large scales. The sensitivities of VIs to different parameters are analyzed on the basis of PROSPECT-SAIL (PROSAIL) radiative transfer model simulations, which apply for homogeneous canopies, and random forest (RF) learning. Specifically, combined factors such as canopy chlorophyll content (CCC) and canopy water content (CWC) are introduced...
ABSTRACT Refractivity happens due to stratification in the lower boundary layer over oceans due t... more ABSTRACT Refractivity happens due to stratification in the lower boundary layer over oceans due to variability of moisture, temperature, wind and sea surface temperature which collectively may lead to generate evaporation duct. The evaporation duct has a significant impact on the spread of electromagnetic waves in the atmosphere over oceans both from the meteorological and military point of view. This ducting sometimes supports normal propagation of radar signals and sometimes may cause distortion and attenuation of signals depending on the height of evaporation duct. This leads to over-estimation and under-estimation of rainfall by weather radar meteorologically and for other targets militarily. The aim of this study was not only to locate evaporation duct height but also to check the efficiency of Weather Research and Forecasting Model (WRF) and Babin’s model so that results may be used in applying correction measures for precise identification of targets by radar. In this study by utilizing the high vertical resolution of WRF for the simulation of different meteorological parameters, the Babin’s method was used for calculating the evaporation duct height over South China Sea for the two months, April and July. Very clear duct heights were calculated at different areas over sea in different time domains. Study reveals that maximum height existed in the month of April although July was rich with different EDHs in different regions in contrast to April. It was found that in most of the cases EDH was higher or maximum when relative humidity was comparatively lower and air temperature and wind speed were comparatively higher. This study paves a way for futuristic study of evaporation duct monitoring and forecasting by assimilation of remote sensing data especially through that of Geostationary satellites by incorporating verification measures from radar
Uploads
Papers