A normalized difference vegetation index (NDVI) time-series of idle agriculture lands: A preliminary study

In this paper, the NDVI time-series collected from the study area between year 2003 and 2005 of all land cover types are plotted and compared. The study area is the agricultural zones in Banphai District, Khonkean, Thailand. The LANDSAT satellite images of different dates were first transformed into a time series of Normalized Difference Vegetation Index (NDVI) images before the investigation. It can be visually observed that the NDVI time series of the Idle Agriculture Land (IAL) has the NDVI values closed to zero. In other words, the trend of the NDVI values remains, approximately, unchanged about the zero level for the whole period of the study time. In contrast, the non-idle areas hold a higher level of the NDVI variation. The NDVI values above 0.5 can be found in these non-idle areas during the growing seasons. Thus, it can be hypothesized that the NDVI time-series of the different land cover types can be used for IAL classification. This outcome is a prerequisite to the follow-up study of the NDVI pattern classification that will be done in the near future

A review of applying second-generation wavelets for noise removal from remote sensing data.

The processing of remotely sensed data includes compression, noise reduction, classification, feature extraction, change detection and any improvement associated with the problems at hand. In the literature, wavelet methods have been widely used for analysing remote sensing images and signals. The second-generation of wavelets, which is designed based on a method called the lifting scheme, is almost a new version of wavelets, and its application in the remote sensing field is fresh. Although first-generation wavelets have been proven to offer effective techniques for processing remotely sensed data, second-generation wavelets are more efficient in some respects, as will be discussed later. The aim of this review paper is to examine all existing studies in the literature related to applying second-generation wavelets for denoising remote sensing data. However, to make a better understanding of the application of wavelet-based denoising methods for remote sensing data, some studies that apply first-generation wavelets are also presented. In the part of hyperspectral data, there is a focus on noise removal from vegetation spectrum

Co-Regulations of Spartina alterniflora Invasion and Exogenous Nitrogen Loading on Soil N2O Efflux in Subtropical Mangrove Mesocosms

We thank Zhonglei Wang, Cunxin Ning, Hui Chen, Qian Huang, Fang Liu and Jian Zhou for their assistance with the greenhouse experiments and gas sampling. We are also grateful to Weimin Song, Rashid Rafique, Junyi Liang, Zheng Shi and Jianyang Xia for editing the manuscript.Both plant invasion and nitrogen (N) enrichment should have significant impact on mangrove ecosystems in coastal regions around the world. However, how N2O efflux in mangrove wetlands responds to these environmental changes has not been well studied. Here, we conducted a mesocosm experiment with native mangrove species Kandelia obovata, invasive salt marsh species Spartina alterniflora, and their mixture in a simulated tide rotation system with or without nitrogen addition. In the treatments without N addition, the N2O effluxes were relatively low and there were no significant variations among the three vegetation types. A pulse loading of exogenous ammonium nitrogen increased N2O effluxes from soils but the stimulatory effect gradually diminished over time, suggesting that frequent measurements are necessary to accurately understand the behavior of N-induced response of N2O emissions. With the N addition, the N2O effluxes from the invasive S. alterniflora were lower than that from native K. obovata mesocosms. This result may be attributed to higher growth of S. alterniflora consuming most of the available nitrogen in soils, and thus inhibiting N2O production. We concluded that N loading significantly increased N2O effluxes, while the invasion of S. alterniflora reduced N2O effluxes response to N loading in this simulated mangrove ecosystem. Thus, both plant invasion and excessive N loading can co-regulate soil N2O emissions from mangrove wetlands, which should be considered when projecting future N2O effluxes from this type of coastal wetland.Yeshttp://www.plosone.org/static/editorial#pee

Consideration of smoothing techniques for hyperspectral remote sensing

Spectral smoothing filters are popularly used in a large number of modern hyperspectral remote sensing studies for removing noise from the data. However, most of these studies subjectively apply ad hoc measures to select filter types and their parameters. We argue that this subjectively minded approach is not appropriate for choosing smoothing methods for hyperspectral applications. In our case study, it is proved that smoothing filters can cause undesirable changes to statistical characteristics of the spectral data; thereby, affecting the results of the analyses that are based on statistical class models. If preserving statistical properties of the original hyperspectral data is desired, smoothing filters should then be used, if necessary, after careful consideration of which smoothing techniques will minimize disturbances to the statistical properties of the original data. A comparative t-test is proposed as a method for choosing a smoothing filter suitable for hyperspectral data at hand

Tropical mangrove species discrimination using hyperspectral data: A laboratory study

The aim of this study is to test whether spectra of crown canopy leaves of various tropical mangrove species measured under laboratory conditions contain sufficient spectral information for discriminating mangroves at the species level. This laboratory-level study is one of the most important prerequisites to the future use of airborne and satellite hyperspectral sensors for mangrove studies. First, spectral responses of 16 Thai tropical mangrove species (2151 spectral bands between 350 nm and 2500 nm) were recorded from the leaves, using a spectrometer under laboratory conditions. Next, the mangrove spectra were statistically tested using one-way ANOVA to see whether they significantly differ at every spectral location. Finally, the spectral separability between each pair of mangrove species was quantified using the Jeffries¿Matusita (J¿M) distance measure. It turned out that the 16 mangrove species under study were statistically different at most spectral locations, with a 95% confidence level (p <0.05). The total number of spectral bands that had p-values less than 0.05 was 1941, of which 477 bands had a 99% confidence level (p <0.01). Moreover, the J¿M distance indices calculated for all pairs of the mangrove species illustrated that the mangroves were spectrally separable except the pairs that comprised the members of Rhizophoraceae. Although the difficulties of discriminating the members of Rhizophoraceae are expected, the overall result encourages further investigations into the use of on-board hyperspectral sensors to see whether mangrove species can be separated when the difficulties of the field conditions are taken into account

A hyperspectral band selector for plant species discrimination

The use of genetic search algorithms (GA) as spectral band selectors is popular in the field of remote sensing. Nevertheless, class information that has been used in the existing research for testing the performance of the GA-based band selector is broad (i.e. Anderson's level I or II). This means that each class possesses distinct spectral characteristics from one another, and it is relatively easy for the band selector to find spectral bands that maintain high spectral separability between classes. None of the existing studies has tested the band selector on class information that possesses very similar spectral characteristics (e.g. species-level data). A question therefore remains if the band selector can deal with such complexity. As a result, the key hypothesis of this research is that the GA-based band selector can be used for selecting a meaningful subset of spectral bands that maintains spectral separability between species classes. The testing data in use are very high-dimensional, spectrometer records that comprise 2151 bands of leaf spectra of 16 tropical mangrove species. The results turned out that the GA-based band selector was able to cope with spectral similarity at the species level. It meaningfully selected spectral bands that related to principal physio-chemical properties of plants, and, simultaneously, maintained the separability between species classes at a high level

Impact of solid shrimp pond waste materials on mangrove growth and mortality: a case study from Pak Phanang, Thailand

One of the most serious threats to tropical mangrove ecosystems caused by shrimp farming activities is the poor management of pond wastematerials.We hypothesise thatmangroves can tolerate chemical residues discharged from shrimp farms and can be used as biofilters, but the capability of mangroves to cope with solid sediments dredged from shrimp ponds is limited. Our study in Pak Phanang, Thailand, confirmed that the excess sediments discharged from nearby shrimp ponds reduced mangrove growth rates and increased mortality rates. A series of transformed multitemporal satellite images was used in combination with the field data to support this claim.In addition, a comparison between four dominant mangrove species revealed that Avicennia marina could tolerate sedimentation rates of >6 cm year¿1, while Bruguiera cylindrica tolerated sedimentation rates of 5 cm year¿1 (total sediment depth = 25 cm) before dying, while Excoecaria agallocha and Lumnitzera racemosa performed intermediate. This outcome implied that in our situation A. marina and to lesser extent E. agallocha and L. racemosa could be more effective as biofilters than B. cylindrica, as theymay survive the sedimentation longer in the disposal areas. Further studies on the impact of sedimentation and chemical pollution of shrimp farmwastes on mangrove mortality and growth are required