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Growth, Structural Transformation, and Rural Change in Viet Nam: A Rising Dragon on the Move

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Book Series: WIDER Studies in Development Economics ISBN: 9780198796961 Year: Pages: 336 DOI: 10.1093/acprof:oso/9780198796961.001.0001 Language: English
Publisher: Oxford University Press Grant: UNU WIDER
Subject: Economics --- History --- Migration
Added to DOAB on : 2017-04-07 11:02:22
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Abstract

Many developing countries—Viet Nam included—continue to struggle to raise incomes per capita. A common feature of the growth and development process is a fundamental change in the pattern of economic activity, as households reallocate labour from traditional agriculture to more productive forms of agriculture and modern industrial and service sectors. Broad structural transformation and widespread poverty reduction is the combined result of these large-scale shifts in work and labour allocation when they realize desired development goals. The roots of this book grow from when the first pilot Viet Nam Access to Resources Household Survey (VARHS) was carried out in 2002. The success of this inspired the Central Institute of Economic Management (CIEM) in Hanoi, the Institute of Policy and Strategy for Agriculture and Rural Development (CAP-IPSARD), the Institute of Labour Science and Social Affairs (ILSSA), and the Development Economics Research Group (DERG) of the University of Copenhagen, together with Danida and, later on, UNU-WIDER, to plan and carry out a more ambitious VARHS from 2006, increasing coverage and representativeness to more than 2,150 families and 12 provinces across the various regions of Viet Nam. The VARHS covering these very same households had, by 2014, been carried out five times, that is, every two years. It is on this high-quality panel data foundation and almost fifteen years of study and policy work using the VARHS data that the present volume builds, in its effort to bring out the essential rural microeconomic characteristics and insights of a dynamic South-East Asian economy in transition from a centrally planned towards a more market-based economy.

Remote Sensing of Leaf Area Index (LAI) and Other Vegetation Parameters

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ISBN: 9783039212392 / 9783039212408 Year: Pages: 334 DOI: 10.3390/books978-3-03921-240-8 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General)
Added to DOAB on : 2019-12-09 11:49:15
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Abstract

Monitoring of vegetation structure and functioning is critical to modeling terrestrial ecosystems and energy cycles. In particular, leaf area index (LAI) is an important structural property of vegetation used in many land surface vegetation, climate, and crop production models. Canopy structure (LAI, fCover, plant height, and biomass) and biochemical parameters (leaf pigmentation and water content) directly influence the radiative transfer process of sunlight in vegetation, determining the amount of radiation measured by passive sensors in the visible and infrared portions of the electromagnetic spectrum. Optical remote sensing (RS) methods build relationships exploiting in situ measurements and/or as outputs of physical canopy radiative transfer models. The increased availability of passive (radar and LiDAR) RS data has fostered their use in many applications for the analysis of land surface properties and processes, thanks also to their insensitivity to weather conditions and the capability to exploit rich structural and textural information. Data fusion and multi-sensor integration techniques are pressing topics to fully exploit the information conveyed by both optical and microwave bands.

Keywords

conifer forest --- leaf area index --- smartphone-based method --- canopy gap fraction --- terrestrial laser scanning --- forest inventory --- density-based clustering --- forest aboveground biomass --- root biomass --- tree heights --- GLAS --- artificial neural network --- allometric scaling and resource limitation --- structure from motion (SfM) --- 3D point cloud --- remote sensing --- local maxima --- fixed tree window size --- managed temperate coniferous forests --- point cloud --- spectral information --- structure from motion (SfM) --- unmanned aerial vehicle (UAV) --- chlorophyll fluorescence (ChlF) --- drought --- Mediterranean --- photochemical reflectance index (PRI) --- photosynthesis --- R690/R630 --- recovery --- BAAPA --- remote sensing --- household survey --- forest --- farm types --- automated classification --- sampling design --- adaptive threshold --- over and understory cover --- LAI --- leaf area index --- EPIC --- simulation --- satellite --- MODIS --- biomass --- evaluation --- southern U.S. forests --- VIIRS --- leaf area index (LAI) --- Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) --- MODIS --- consistency --- uncertainty --- evaluation --- downscaling --- Pléiades imagery --- unmanned aerial vehicle --- stem volume estimation --- remote sensing --- clumping index --- leaf area index --- trunk --- terrestrial LiDAR --- HemiView --- forest above ground biomass (AGB) --- polarization coherence tomography (PCT) --- P-band PolInSAR --- tomographic profiles --- canopy closure --- global positioning system --- hemispherical sky-oriented photo --- signal attenuation --- geographic information system --- digital aerial photograph --- aboveground biomass --- leaf area index --- photogrammetric point cloud --- recursive feature elimination --- machine-learning --- forest degradation --- multisource remote sensing --- modelling aboveground biomass --- random forest --- Brazilian Amazon --- validation --- phenology --- NDVI --- LAI --- spectral analyses --- European beech --- altitude --- forests biomass --- remote sensing --- REDD+ --- random forest --- Tanzania --- RapidEye

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