However, in areas with high leaf area index lai, vegetation indices usually. Information on the state of the terrestrial vegetation cover is important for several ecological, economical, and planning issues. Considering the temporal resolution and data acquisition costs, digital aerial photographs daps from a digital camera mounted on an unmanned aerial vehicle or light. Forest leaf area index inversion based on landsat oli data in the. In this study, optical remote sensing data were used for leaf area index lai estimation. Leaf area index lai is an important index for evaluating winter wheats growth status and forecasting its yield. Liang 2009 scale transformation of leaf area index product retrieved from multiresolution remotely sensed data. Special issue leaf area index lai retrieval using remote sensing. This special issue, leaf area index lai retrieval using remote sensing, is calling for papers that demonstrate original research that can overcome or address the above challenges and gaps and develop corresponding solutions, in particular using remote sensing recent advances.
The combination of a poor 20142015 season, the extremely dry early agricultural season. Theories, methods and sensors article pdf available in sensors 94. Ieee transactions on geoscience and remote sensing, 52, pp. Remotely sensed images including landsat, spot, naip orthoimagery, and lidar and relevant processing tools can be used to predict plant stomatal conductance g s, leaf area index lai, and canopy. Fpar is defined as the fraction of incident photosynthetically active radiation 400700 nm absorbed by the green elements of a vegetation canopy. Sea surface temperature remote sensing reflectance. Leaf area index retrieval combining hj1ccd and landsat8oli data in the. In conifers, three definitions for lai have been used. An indexdatabase idb could be an useful tool to find indices for a required application, adapted to a selected sensor. Mod15a2h modis leaf area indexfpar 8day l4 global 500m sin grid.
Fpar is the fraction of photosynthetically active radiation 400700 nm absorbed by green vegetation. Downloaded from spie digital library on 18 jul 2012 to 128. Stomatal conductance, canopy temperature, and leaf area. Remotely sensed images including landsat, spot, naip orthoimagery, and lidar and relevant processing tools can be used to predict plant stomatal conductance g. Estimation of forest leaf area index using remote sensing. Remote sensing of environment, 171, 105117 2xiao, z. Lai can also be estimated from remotesensing data using either statistical or physical methods.
Considering the temporal resolution and data acquisition costs, digital aerial photographs daps from a digital camera mounted on an unmanned aerial. Global data sets of vegetation leaf area index lai3g and. Estimation of forest canopy leaf area index using modis. Ground data, including biomass and leaf area index, were collected monthly at the rangeland site and weekly or triweekly at the crop site. Leaf area index retrieval using high resolution remote sensing data by michele rinaldi, sergio ruggieri, pasquale garofalo, alessandro vittorio vonella, giuseppe satalino and pietro soldo no static citation data no static citation data cite. Therefore, the purpose of this study is to estimate the lai through remote sensing. Remote sensing free fulltext leaf area index retrieval.
The amount and spatial and temporal dynamics of vegetation are important information in environmental studies and agricultural practices. Example uses of the database for global plant productivity, fractional energy absorption, and remote sensing studies are highlighted. Comparison of two inversion methods for winter wheat leaf. Lai is defined as the onesided green leaf area per unit ground area in broadleaf canopies and as half the total needle surface area per unit ground area in coniferous canopies. The aim of this study is to evaluate the accuracy of leaf area index lai retrieval over agricultural area that can be obtained by empirical relationships between different spectral vegetation indices vi and lai measured on three. Estimation of forest leaf area index using remote sensing and. Leaf area index retrieval using high resolution remote sensing data by pietro soldo, giuseppe satalino, alessandro vittorio vonella, pasquale garofalo, michele rinaldi and sergio ruggieri no static citation data no static citation data cite. Leaf area index lai is a dimensionless quantity that characterizes plant canopies. Lai extracted from remotely sensed data may contribute to grasp the yield of rice at an early stage. Pdf retrieving leaf area index lai using remote sensing. Imaging spectrometer chris were acquired to derive leaf area index information. Leaf area index is an indicator of the density of vegetation, and is relatively easy to measure. Lai is defined as the onesided green leaf area per unit ground area in. A visible band index for remote sensing leaf chlorophyll content at the canopy scale.
In a recent article, bausch 1993 described the derivation of crop water use coefficients from visible and nearinfrared reflectance data, as well as various radiometric vegetation indices such as the normalized difference vegetation index ndvi. Leaf area index retrieval using high resolution remote sensing data. Citeseerx derivation of forest leaf area index from multi. In this regard, vegetation properties such as the type, vitality, or density can be described by means of continuous biophysical parameters. Estimation of forest leaf area index using remote sensing and gis data for modelling net primary production. The data provide input to terrestrial ecosystem and land. Remote sensing of leaf area index and clumping index.
Available bands of sensors are linked with required wavelenghts of indices, so that one can get all sensors usable for calculating an index and vice versa one can find all indices that can be calculated by data from a specific sensor. The main aim of this study was to analyze retrieval accuracy of soybean leaf area index lai based on multisource remote sensing data including ground hyperspectral, unmanned aerial vehicle uav multispectral and the gaofen1 gf1 wfv. A methodology for estimating leaf area index by assimilating remote sensing data into crop model based on temporal and spatial knowledge. Calculation by combining multispectral data and insitu measurements use different methods than ones based on highres lidar data or hyperspectral images. One of these parameters is the leaf area index lai, which is defined as half the total leaf area per unit. Stomatal conductance, canopy temperature, and leaf area index estimation using remote sensing and obia techniques s. The relationship between the normalized difference vegetation index ndvi and leaf area index lai during the season and yield of the storage root in autumn was studied. Lai is defined as the onesided green leaf area per unit ground area in broadleaf canopies and as onehalf the total needle surface area per unit ground area in coniferous canopies.
Due to a wide variety in spatial resolution of remotely sensed data and the requirements of ecological modeling, the scaling. Comparison of inversion method of maize leaf area index. Retrieval of leaf area index using temporal, spectral, and. Lai can also be estimated from remote sensing data using either statistical or physical methods. With the innovation of remote sensing technology, remote sensing data sources are more and more abundant. The estimation of biophysical variables, such as the leaf area index lai, using remote sensing techniques, is still the subject of numerous studies, since these variables allow obtaining. A large number of relationships have been discovered between remote sensing data obtained from optical, thermal, lidar, and radar sensors at. Comparison of precision in retrieving soybean leaf area.
Leaf area index retrieval using high resolution remote. The 10day data for entire canada and the envi header files can be downloaded here see below. Integrating remote sensing data on evapotranspiration and. Data from the four instruments were corrected for the varying seasonal and geographic atmospheric conditions present along.
This ratio can be related to gasvegetation exchange processes such as photosynthesis 1, evaporation and transpiration 2 4, rainfall interception 5, and carbon flux 6. Scaling effect of leaf area index lai in remote sensing field means that values of lai derived from different resolutions images also differ. An important vegetation biophysical parameter, the leaf area index lai, is a dimensionless variable and a ratio of leaf area to per unit ground surface area. Leaf area index retrieval using hyperion eo1 data based vegetation indices in himalayan forest system 2 recommendations 29th jul, 2016. Estimating the fraction of absorbed photosynthetically active radiation from the modis data based glass leaf area index product.
Estimation of forest aboveground biomass and leaf area index. This definition is especially applicable to flat broad leaf condition with same area on both sides of leaf. Leaf area index lai is an important essential biodiversity variable due to its role in many ecosystem processes such as terrestrial evapotranspiration, energy balance, and gas exchanges as well as plant growth potential. This chapter first introduces field methods for measuring lai. University of trier, remote sensing department, trier, germany keywords. Leaf area index estimates using remotely sensed data and.
Leaf area index lai is a key parameter in most land surface models. Validation and intercomparison of global leaf area index products derived from remote sensing data s. The foundation of discussing lai scaling effect problem is accurately retrieving lai values from remote sensing images, and trying to exclude the. Comparison of inversion method of maize leaf area index based. Jan 01, 2011 the journal of applied remote sensing jars is an online journal that optimizes the communication of concepts, information, and progress within the remote sensing community to improve the societal benefit for monitoring and management of natural disasters, weather forecasting, agricultural and urban landuse planning, environmental quality monitoring, ecological restoration, and numerous. Derivation of forest leaf area index from multi and. Stomatal conductance, canopy temperature, and leaf area index. Remote sensing of seasonal leaf area index across the.
Leaf area index estimation in a heterogeneous grassland using optical, sar, and dem data. Estimation of forest aboveground biomass and leaf area. A good relationship was observed between groundbased and remote sensing derived leaf area index in the case of wheat r2. On this site you find a database of remote sensing indices and satellite sensors. Retrieving leaf area index lai using remote sensing. Firstly, sensitive parameters of crop model were calibrated by shuffled complex evolution method developed at the university of arizona sceua optimization method based on phenological information, which is called temporal. Leaf area index estimation in a heterogeneous grassland using.
The journal of applied remote sensing jars is an online journal that optimizes the communication of concepts, information, and progress within the remote sensing community to improve the societal benefit for monitoring and management of natural disasters, weather forecasting, agricultural and urban landuse planning, environmental quality monitoring. Leaf area index estimation from hyperspectral data using. Potential of high resolution remote sensing data for leaf. Leaf area index is defined as the projected area of leaves over a unit of land m2 m. Improving regional winter wheat yield estimation through. It is defined as the onesided green leaf area per unit ground surface area lai leaf area ground area, m2 m2 in broadleaf canopies. Leaf area index lai is an important index that reflects the growth status of. Estimation of forest canopy leaf area index using modis, misr.
Leaf area index lai indicates the amount of leaf area in an ecosystem. The dynamic leaf area index lai derived from satellite remote sensing was incorporated into the variable infiltration capacity model vic to enable an interannually varying seasonal cycle of vegetation vicveg. As a fundamental plant parameter leaf area index lai leaf area ground surface. Remotely sensed data acquired from four remotesensing instruments on three different aircraft platforms over a transect of coniferous forest stands in oregon were analyzed with respect to seasonal leaf area index lai. With darwin sp data acquisition software included, it provides instant access to 19 vegetation indices for your research. Firstly, sensitive parameters of crop model were calibrated by shuffled complex evolution method developed at the university of arizona sceua optimization method based on phenological. The triangular greenness index tgi was developed based on the area of a triangle surrounding the spectral features of chlorophyll with points at 670nm, r670, 550nm, r550, and 480nm, r480, where r. A failure to develop an approach that has these advantages, but cir occurs when the optimization algorithm does not find an. Remote sensing of leaf area index lai and a spatiotemporally parameterized model for mixed grasslands li shen zhaoqin li xulin guo department of geography and planning university of saskatchewan saskatoon, sk s7n5c8, canada abstract leaf area index lai is an important biophysical variable used to reflect the vegetation condition in ecosystems. In reality, the shape of leaves is not always of this type, some leaves such as white spruce picea glauca are needleshaped. It is of great significance to estimate agb and lai accurately using remote sensing technology.
Validation and intercomparison of global leaf area index. The current inversion method of maize leaf area index has the problems of long timeconsuming inversion, high energy consumption, and low fitting coefficient between the prediction result and the actual result. This study aimed at estimating whether differences in leaf area development of sugar beet resulting from different agronomic practices can be determined with remote sensing. For these problems, an inversion method of maize leaf area index based on uav hyperspectral remote sensing is proposed in this paper. Until now, lai research focused either on the use of coarse resolution remote sensing data for global applications, or on lai modeling over a confined area, mostly in forest and crop ecosystems, using medium to high spatial resolution data. The lai is an important measure to increase the yield and adjust the quantity of manure. Leaf area index estimation in a heterogeneous grassland. Hyperspectral remote sensing is a new technical approach that can be used to acquire the information of winter wheat lai immediately. Half of the total needle surface area per unit ground surface area. Improved lai algorithm implementation to modis data by incorporating background, topography, and foliage clumping information. How to calculate lai leaf area index using remote sensing. How to calculate lai leaf area index in remote sensing. The parameters inverted in step 1 are then passed to a quality control procedure, which checks the parameter boundary conditions to detect inversion failures. As shown in table 1, total leaf area index tolai was first defined as the total onesided area of photosynthetic tissue per unit ground surface area 51,52.
Both variables are used for calculating surface photosynthesis. Leaf area index estimation from visible and nearinfrared. Monika moskal remote sensing and geospatial analysis laboratory and precision forestry cooperative, college of forest resources, university of washington, box 352100, seattle, washington, usa 981952100. Citeseerx document details isaac councill, lee giles, pradeep teregowda. Changes in canopy cover with nasa modis leaf area index data. Leaf area index lai and the fraction of photosynthetically active. It is defined as the onesided green leaf area per unit ground surface area lai leaf area ground area, m 2 m 2 in broadleaf canopies. Introduction monitoring and modeling global vegetation dynamics in the context of climate variability and change studies require longterm data sets of key biophysical variables that characterize vegetation structure and functioning 1. Weissinfluence of landscape spatial heterogeneity on the nonlinear estimation of leaf area index from moderate spatial resolution remote sensing data remote sens. This study evaluated systematically linear predictive models between vegetation indices vis derived from radiometrically corrected airborne imaging spectrometer hymap data and field measurements of. Leaf area index estimates using remotely sensed data and brdf. Citeseerx derivation of forest leaf area index from.
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