Relating Radar Remote Sensing of Biomass to Modelling of Forest Carbon Budgets

This paper addresses the use of radar remote sensing to map forest above-ground biomass, and discusses the use of biomass maps to test a dynamic vegetation model that identifies carbon sources and sinks and predicts their variation over time. For current radar satellite data, only the biomass of young/sparse forests or regrowth after disturbances can be recovered. An example from central Siberia illustrates that biomass can be measured by radar at a continental scale, and that a significant proportion of the Siberian forests have biomass values less than 50 tonnes/ha. Comparison between the radar map and calculations by the Sheffield Dynamic Global Vegetation Model (SDGVM) indicates that the model considerably overestimates biomass; under-representation of managed areas, disturbed areas and areas of low site quality in the model are suggested reasons for this effect. A case study carried out at the Büdingen plantation forest in Germany supports the argument that inadequate representations of site quality and forest management may cause model overestimates of biomass. Comparison of the calculated biomass of stands planted after 1990 with biomass estimates by radar allows identification of forest stands where the growth conditions assumed by the model are not valid. This allows a quality check on model calculations of carbon fluxes: only calculations for stands where there is good agreement between the data and the model predictions should be accepted. Although the paper only uses the SDGVM model, similar effects are likely in other dynamic vegetation models, and the results show that model calculations attempting to quantify the role of forests as carbon sources or sinks could be qualified and potentially improved by exploiting remotely sensed measurements of biomass.     

Seismic Network,Seismic Activity and Seismological Research of Vietnam

In this paper,a historical review of the seismic network of Vietnam and the ability of the network to monitor earthquakes is presented.The seismic activity of Vietnam as a country of high seismictiy in the last century and since the beginning of the new century is described.The current state of seismological research in Vietnam and cooperation with institutions outside of Vietnam is outlined.     

Predicting soil erosion hazard in Lattakia Governorate(W Syria)

The main objective of this study is to predict soil erosion in the Lattakia Governorate(WSyria)using the Water Erosion Prediction Project model(WEPP)and to compare the result with that of the RUSLE.Field survey and data collection were carried out,and 44 soil samples were analyzed.In addition,all the necessary input files were prepared for use in the WEPP model and RUSLE.Results show that more than of 80%of the locations studied experience slight to moderate erosion(less than 5 t/ha/y),whereas the rest of the locations experience severe soil erosion hazard.Moreover,the volume of runoff estimated by the WEPP model is in the range of 51e321 mm,and the R^2 between the simulated soil erosion and the predicted runoff reached 0.68.Interestingly,the R^2 between the WEPP model and RUSLE is 0.56,which indicates a good correlation between the two models.     

Application of multimedia methodology for investigation of karst water in highland regions of Ha Giang Province, Vietnam

Ha Giang is one of the largest, northern border provinces of Vietnam, consisting of four districts: Yen Minh, Quan Ba, Dong Van and Meo Vac. This province features varied karst landscape of Carboniferous–Permian limestone. The region has been recognized by UNESCO as one of the 77 geological parks in the world and the second in Southeast Asia on 3 October 2012. In the dry season, little or no rain is recorded; therefore, surface water is very scarce. For this reason, proper delineation and exploitation of the groundwater resource is critical for sustainable water supply. This has been identified as an important challenge under the scientific project KC-08-10 in the national program KC-08. Remote sensing and GIS were used to decipher the signature of karst water in the highland of Ha Giang. Information layers generated were subjected to multi-criteria evaluation using analytic hierarchy process for decision making to identify ideal locations for groundwater prospecting. The study resulted in delineation of ten zones for all regions and 18 ideal drilling sites in Tam Son Town of Quan Ba District. Drilling and resistivity soundings were performed to assess the success of the interpretation. Deep resistivity survey confirmed low resistivity (200–300 Ωm) near the identified potential sites in Tam Son Town of Quan Ba District. Further, successful drilling at site LKTS1 with a discharge of 7–9 l/s is observed, proving the potential of this methodology for rapid exploration of groundwater in water-scare karst terrains of Vietnam.     

Relating Radar Remote Sensing of Biomass to Modelling of Forest Carbon Budgets

This paper addresses the use of radar remote sensing to map forest above-ground biomass, and discusses the use of biomass maps to test a dynamic vegetation model that identifies carbon sources and sinks and predicts their variation over time. For current radar satellite data, only the biomass of young/sparse forests or regrowth after disturbances can be recovered. An example from central Siberia illustrates that biomass can be measured by radar at a continental scale, and that a significant proportion of the Siberian forests have biomass values less than 50 tonnes/ha. Comparison between the radar map and calculations by the Sheffield Dynamic Global Vegetation Model (SDGVM) indicates that the model considerably overestimates biomass; under-representation of managed areas, disturbed areas and areas of low site quality in the model are suggested reasons for this effect. A case study carried out at the Büdingen plantation forest in Germany supports the argument that inadequate representations of site quality and forest management may cause model overestimates of biomass. Comparison of the calculated biomass of stands planted after 1990 with biomass estimates by radar allows identification of forest stands where the growth conditions assumed by the model are not valid. This allows a quality check on model calculations of carbon fluxes: only calculations for stands where there is good agreement between the data and the model predictions should be accepted. Although the paper only uses the SDGVM model, similar effects are likely in other dynamic vegetation models, and the results show that model calculations attempting to quantify the role of forests as carbon sources or sinks could be qualified and potentially improved by exploiting remotely sensed measurements of biomass.     

Gendered access to customary land in East Timor

Land tenure rights reflect the deeper structures of society, particularly gender distinctions in relation to land. Considering the structural differences between patrilineal and matrilineal customary tenure systems in East Timor are understudied, this paper explores men and women’s experiences in accessing land under such arrangements. The comparative analysis of two patrilineal with one matrilineal land tenure systems in Ainaro and Manufahi districts suggests a significant degree of flexibility within both systems with respect to the norms of gendered inheritance. Therefore, the binary constructs of ‘patrilineal’ and ‘matrilineal’ societies are limiting. Both men and women in these communities may acquire land rights under different circumstances, mainly through negotiations with their parents or hamlet chief. Daughters in the patrilineal communities could inherit family land upon their parents’ death and sons in the matrilineal community could gain land by cultivating and maintaining unclaimed customary land. Empirical evidence show that inheritance principally determines usufruct rights to land, but marriage exchange practices complicates a deeper understanding of traditional East Timorese land rights.

Credibility of design rainfall estimates for drainage infrastructures: extent of disregard in Nigeria and proposed framework for practice

Natural Hazards - Rainfall intensity or depth estimates are vital input for hydrologic and hydraulic models used in designing drainage infrastructures. Unfortunately, these estimates are...     

GIS-based landslide susceptibility modeling: A comparison between fuzzy multi-criteria and machine learning algorithms

Hazards and disasters have always negative impacts on the way of life.Landslide is an overwhelming natural as well as man-made disaster that causes loss of natural resources and human properties throughout theworld.The present study aimed to assess and compare the prediction efficiency of different models in landslide susceptibility in the Kysuca river basin,Slovakia.In this regard,the fuzzy decision-making trial and evaluation laboratory combining with the analytic network process(FDEMATEL-ANP),Na?ve Bayes(NB)classifier,and random forest(RF)classifier were considered.Initially,a landslide inventory map was produced with 2000 landslide and nonlandslide points by randomly dividedwith a ratio of 70%:30%for training and testing,respectively.The geospatial database for assessing the landslide susceptibility was generated with the help of 16 landslide conditioning factors by allowing for topographical,hydrological,lithological,and land cover factors.The ReliefF methodwas considered for determining the significance of selected conditioning factors and inclusion in the model building.Consequently,the landslide susceptibility maps(LSMs)were generated using the FDEMATEL-ANP,Na?ve Bayes(NB)classifier,and random forest(RF)classifier models.Finally,the area under curve(AUC)and different arithmetic evaluation were used for validating and comparing the results and models.The results revealed that random forest(RF)classifier is a promising and optimum model for landslide susceptibility in the study area with a very high value of area under curve(AUC=0.954),lower value of mean absolute error(MAE=0.1238)and root mean square error(RMSE=0.2555),and higher value of Kappa index(K=0.8435)and overall accuracy(OAC=92.2%).     

Vortex initialization for typhoon track prediction

Summary A shallow water single level primitive equation model is ideally suited for studying the motion of a tropical cyclone. Three factors seem to be important in the initialization, i.e. the size, intensity and the initial speed and direction of motion of the storm. This study presents the results of sensitivity studies on the above parameters in the definition of a synthetic idealized vortex. The sensitivity studies include results of experimental forecasts for typhoons Betty of 1987 and Dan of 1989. The results of these studies show that the initial size, intensity and direction and speed of motion show considerable sensitivity to the predicted track. Finally a summary of the track forecast errors through 72 hours are presented for these storms.With 8 Figures