Kensuke Kawamura

Evaluation of ASTER GDEM2 in Comparison with GDEM1, SRTM DEM and Topographic-Map-Derived DEM Using Inundation Area Analysis and RTK-dGPS Data

This study evaluates the quality of the Advanced Spaceborne Thermal Emission Radiometer-Global Digital Elevation Model version 2 (ASTER GDEM2) in comparison with the previous version (GDEM1) as well as the Shuttle Radar Topographic Mission (SRTM) DEM and topographic-map-derived DEM (Topo-DEM) using inundation area analysis for the projected location of the Karian dam, Indonesia. In addition, the vertical accuracy of each DEM is evaluated using the Real-Time Kinematic differential Global Positioning Systems (RTK-dGPS) data obtained from an intensive geodetic survey. The results of the inundation area analysis show that GDEM2 produced a higher maximum contour level (MCL) (64 m) than did GDEM1 (55 m), and thus, GDME2 has a better quality. In addition, the GDEM2-derived MCL is similar to those produced by SRTM DEM (69 m) and Topo-DEM (62 m). The improvement in the contour level in GDEM2 is believed to be related to the successful removal of voids (artifacts) and anomalies present in GDEM1. However, our RTK-dGPS results show that the vertical accuracy of GDEM2 is much lower than that of GDEM1 and the other DEMs, which is contradictory to the accuracy stated in the GDEM2 validation document. The vertical profiles of all DEMs show that GDEM2 contains a comparatively large number of undulation effects, thereby

Monitoring of forage conditions with MODIS imagery in the Xilingol steppe, Inner Mongolia

A study was conducted to determine the potential suitability of Terra/MODIS imagery for monitoring short‐term phenological changes in forage conditions in a semi‐arid region. The study sites included four meadow steppes and six typical steppes in the Xilingol steppe in central Inner Mongolia, China. The live biomass, dead standing biomass, total biomass, crude protein (CP) concentration and standing CP were estimated from early April to late October using the Enhanced Vegetation Index (EVI) values from Terra imagery (500 m pixels). Applying regression models, the EVI accounted for 80% of the variation in live biomass, 42% of the dead biomass, 77% of the total biomass, 11% of the CP concentration and 74% of the standing CP. MODIS/EVI is superior to AVHRR/NDVI when estimating forage quantity. Applying these results, the seasonal changes in live biomass and the standing CP could be described in the selected four sites with different degrees of grazing intensity. Generally, the increase in grazing intensity tended to decrease live biomass and standing CP. It was suggested that the EVI obtained from Terra imagery was an available predictor of the forage condition as measured by live biomass and standing CP. The MODIS/EVI values could provide information on the suitable timing of cutting for hay‐making and nutritive value to range managers.

Not an ancient relic: the endemic Livistona palms of arid central Australia could have been introduced by humans

Livistona mariae is an endemic palm localized in arid central Australia. This species is separated by about 1000 km from its congener L. rigida, which grows distantly in the Roper River and Nicholson–Gregory River catchments in northern Australia. Such an isolated distribution of L. mariae has been assumed to have resulted from contraction of ancestral populations as Australia aridified from the Mid-Miocene (ca 15 Ma). To test this hypothesis at the population level, we examined the genetic relationships among 14 populations of L. mariae and L. rigida using eight nuclear microsatellite loci. Our population tree and Bayesian clustering revealed that these populations comprised two genetically distinct groups that did not correspond to the current classification at species rank, and L. mariae showed closest affinity with L. rigida from Roper River. Furthermore, coalescent divergence-time estimations suggested that the disjunction between the northern populations (within L. rigida) could have originated by intermittent colonization along an ancient river that has been drowned repeatedly by marine transgression. During that time, L. mariae populations could have been established by opportunistic immigrants from Roper River about 15 000 years ago, concurrently with the settlement of indigenous Australians in central Australia, who are thus plausible vectors. Thus, our results rule out the ancient relic hypothesis for the origin of L. mariae.

Field radiometer with canopy pasture probe as a potential tool to estimate and map pasture biomass and mineral components: A case study in the Lake Taupo catchment, New Zealand

Abstract Precision farming requires data on resource status at a very fine, within‐paddock scale which is impractical to collect by traditional sampling methods. This paper demonstrates the potential of a field radiometer in conjunction with a canopy pasture probe (CAPP) and global positioning system (GPS) to predict and map the spatial distribution patterns of herbage biomass and mass of nutrients, such as nitrogen (N), phosphorous (P), potassium (K), and sulphur (S) in hill country grassland. The accuracy of the calibration model using partial least squares (PLS) regression was assessed by using coefficient of determination (R 2) and the ratio of prediction to standard deviation (RPD). Continuum‐removed derivative reflectance (CRDR) data used in a PLS model gave an excellent prediction of the standing masses of N, P, and S (R 2> 0.895, RPD > 3.0). Both first derivative reflectance (FDR) and CRDR datasets gave a good prediction of standing biomass (R 2 > 0.857, RPD > 2.5). Although relatively lower prediction accuracy was shown in standing K, it may still be possible to make a quantitative prediction using CRDR and FDR (RPD > 2.2). The semivariograms parameter “range” of biomass was longer (58.7 m) than the ranges of the other parameters (10.6–17.4 m), suggesting that biomass values influenced neighbouring values of biomass over greater distances than the other pasture parameters (masses of N, P, K, and S).

Nuclear and chloroplast DNA phylogeography reveals Pleistocene divergence and subsequent secondary contact of two genetic lineages of the tropical rainforest tree species Shorea leprosula (Dipterocarpaceae) in South‐East Asia

Tropical rainforests in South‐East Asia have been affected by climatic fluctuations during past glacial eras. To examine how the accompanying changes in land areas and temperature have affected the genetic properties of rainforest trees in the region, we investigated the phylogeographic patterns of a widespread dipterocarp species, Shorea leprosula. Two types of DNA markers were used: expressed sequence tag‐based simple sequence repeats and chloroplast DNA (cpDNA) sequence variations. Both sets of markers revealed clear genetic differentiation between populations in Borneo and those in the Malay Peninsula and Sumatra (Malay/Sumatra). However, in the south‐western part of Borneo, genetic admixture of the lineages was observed in the two marker types. Coalescent simulation based on cpDNA sequence variation suggested that the two lineages arose 0.28–0.09 million years before present and that following their divergence migration from Malay/Sumatra to Borneo strongly exceeded migration in the opposite direction. We conclude that the genetic structure of S. leprosula was largely formed during the middle Pleistocene and was subsequently modified by eastward migration across the subaerially exposed Sunda Shelf.

Potential for spectral indices to remotely sense phosphorus and potassium content of legume-based pasture as a means of assessing soil phosphorus and potassium fertility status

Precision nutrient management needs analytical tools that aid collection of site-specific data. Adequate soil phosphorus (P) and potassium (K) fertility is crucial for pasture production in New Zealand. This article explores (a) the relationship between 12 spectral indices from in situ canopy reflectance and pasture growth rate (PGR), and pasture P and K content in pastures, (b) the performance of the model in different seasons and (c) the relationship between sensed pasture P and K content and soil P (Olsen P) and K (exchangeable K) fertility. Hyperspectral data were collected from a small area of each of 30 legume-based pastures that varied in soil P (Olsen P 5–72 mg kg−1) and soil exchangeable K (0.20−1.32 cmol kg−1) in spring 2004 and again in summer 2006. Overall, the photochemical reflectance index (PRI) showed the best coefficients of determination (R 2) for most variables. In an exploratory analysis using all the spectral waveband data, normalized difference spectral indices (NDSIs) using the combination of reflectance at 523 and 583 nm of the pasture canopy gave the best prediction of soil P and exchangeable K status. The prediction of Olsen P from plant P (R 2 > 0.89) and soil K from plant K (R 2 > 0.73) was achieved through fitted logarithmic functions that linked plant P and K to soil P and K status, respectively. This pilot study has been broadened to examine other methodologies for interpreting the spectral data and extended to other pasture types and soil orders.

A preliminarily study for predicting body weight and milk properties in lactating Holstein cows using a three-dimensional camera system

Digital imaging has been applied to assess body weight and fatness in livestock.We examine low priced 3D camera for estimating cow body weight and milk properties.Six geodesic line (GL) lengths were computed using back posture 3D object of cow.A similar determination of body condition with standard method is possible. Since manual body condition scoring has been widely utilized as an indirect and subjective method to estimate energy reserves of dairy cattle, image analysis has been increasingly researched for use on large farms as an objective and effective measuring instrument for the estimation of body condition score (BCS) and body weight (BW). Recent advances in the technological development of the three-dimensional (3D) cameras may provide innovative feed management tools for dairy farms. The objective of the present study was to evaluate the feasibility of a 3D camera systems in measuring the back posture of lactating Holstein dairy cows to predict the BCS, BW, milk yield (MY), milk fat (MF) and milk protein (MP). The BCSs for eight cows were recorded by two trained observers using a 5-point scale, and other variables were obtained using an automatic milking system during the lactation. Back posture measurements of dairy cows were conducted using the ASUS Xtion Pro sensor. Six geodesic line (GL) lengths were computed using the 3D objects of each cow based on the positions of the right and left hook bones (GLhh), right and left thurl bones (GLtt), right and left pin bones (GLpp), hook and thurl bones (GLht), hook and pin bones (GLhp), and coccygeal ligament (GLcl). In the principal component analysis (PCA), GL, GLpp, and GLcl had the greatest contribution to principal component values (PCV) 1, 2, and 3, respectively, and these three PCVs described 0.887 of the cumulative contribution ratio. Good correlations were found between the observed and predicted values of BCS (R2=0.74), BW (0.80), MY (0.62), MF (0.62), and MP (0.53) based on linear regression equations using the GLs as explanatory variables and parity (1, 2, and >3) as a fixed effect. These results demonstrate that the 3D cameras could represent an innovative tool for estimating body condition and milk properties.

Mapping herbage biomass and nitrogen status in an Italian ryegrass (Lolium multiflorum L.) field using a digital video camera with balloon system

Improving current precision nutrient management requires practical tools to aid the collection of site specific data. Recent technological developments in commercial digital video cameras and the miniaturization of systems on board low-altitude platforms offer cost effective, real time applications for efficient nutrient management. We tested the potential use of commercial digital video camera imagery acquired by a balloon system for mapping herbage biomass (BM), nitrogen (N) concentration, and herbage mass of N (Nmass) in an Italian ryegrass (Lolium multiflorum L.) meadow. The field measurements were made at the Setouchi Field Science Center, Hiroshima University, Japan on June 5 and 6, 2009. The field consists of two 1.0 ha Italian ryegrass meadows, which are located in an east-facing slope area (230 to 240 m above sea level). Plant samples were obtained at 20 sites in the field. A captive balloon was used for obtaining digital video data from a height of approximately 50 m (approximately 15 cm spatial resolution). We tested several statistical methods, including simple and multivariate regressions, using forage parameters (BM, N, and Nmass) and three visible color bands or color indices based on ratio vegetation index and normalized difference vegetation index. Of the various investigations, a multiple linear regression (MLR) model showed the best cross validated coefficients of determination (R2) and minimum root-mean-squared error (RMSECV) values between observed and predicted herbage BM (R2 = 0.56, RMSECV = 51.54), Nmass (R2 = 0.65, RMSECV = 0.93), and N concentration (R2 = 0.33, RMSECV = 0.24). Applying these MLR models on mosaic images, the spatial distributions of the herbage BM and N status within the Italian ryegrass field were successfully displayed at a high resolution. Such fine-scale maps showed higher values of BM and N status at the bottom area of the slope, with lower values at the top of the slope.

Spectral Index for Quantifying Leaf Area Index of Winter Wheat by Field Hyperspectral Measurements: A Case Study in Gifu Prefecture, Central Japan

Timely and nondestructive monitoring of leaf area index (LAI) using remote sensing techniques is crucial for precise and efficient management of crops. In this paper, a new spectral index (SI) for estimating LAI of winter wheat (Triticum aestivum L.) is proposed on the basis of field hyperspectral measurements. A simple index based on the empirical relationships between LAIs and SIs of all available two-waveband combinations from hyperspectral data is developed by considering the difference between reflectance values at 760 and 739 nm (DSIR760–R739 = R760 – R739). Among published and newly developed SIs, DSIR760–R739 exhibited a significant and strong linear relationship with LAI and showed outstanding performance in LAI assessments. The permissible bandwidths for broad-band DSIR760–R739 investigated using simulated reflectance were 5 nm for both 760 and 739 nm center wavelengths. The results indicate that the linear regression model based on the narrow-band and broad-band DSIR760–R739 is a simple but accurate method for timely and nondestructive monitoring of LAI.

Vis-NIR Spectroscopy and PLS Regression with Waveband Selection for Estimating the Total C and N of Paddy Soils in Madagascar

Visible and near-infrared (Vis-NIR) diffuse reflectance spectroscopy with partial least squares (PLS) regression is a quick, cost-effective, and promising technology for predicting soil properties. The advantage of PLS regression is that all available wavebands can be incorporated in the model, while earlier studies indicate that PLS models include redundant wavelengths, and selecting specific wavebands can refine PLS analyses. This study evaluated the performance of PLS regression with waveband selection using Vis-NIR reflectance spectra to estimate the total carbon (TC) and total nitrogen (TN) in soils collected mainly from the surface of upland and lowland rice fields in Madagascar (n = 59; after outliers were removed). We used iterative stepwise elimination-based PLS (ISE-PLS) to estimate soil TC and TN and compared the predictive ability with standard full-spectrum PLS (FS-PLS). The predictive abilities were assessed using the coefficient of determination (R2), the root mean squared error of cross-validation (RMSECV), and the residual predictive deviation (RPD). Overall, ISE-PLS using first derivative reflectance (FDR) showed a better predictive accuracy than ISE-PLS for both TC (R2 = 0.972, RMSECV = 0.194, RPD = 5.995) and TN (R2 = 0.949, RMSECV = 0.019, RPD = 4.416) in the soil of Madagascar. The important wavebands for estimating TC (12.59% of all wavebands) and TN (3.55% of all wavebands) were selected from all 2001 wavebands over the 400–2400 nm range using ISE-PLS. These findings suggest that ISE-PLS based on Vis-NIR diffuse reflectance spectra can be used to estimate soil TC and TN contents in Madagascar with an improved predictive accuracy.