Litter production and leaf nutrient concentration and remobilization in response to climate seasonality in the central Amazon

Litterfall is the largest source of nutrients to for-est soils of tropical rainforests.However,variability in lit-terfall production,nutrient remobilization,and changes in leaf nutrient concentration with climate seasonality remain largely unknown for the central Amazon.This study meas-ured litterfall production,leaf nutrient remobilization,and leaf area index on a forest plateau in the central Amazon.Litterfall was measured at monthly intervals during 2014,while nitrogen,phosphorus,potassium,calcium and mag-nesium concentrations of leaf litter and canopy leaves were measured in the dry and rainy seasons,and remobilization rates determined.Leaf area index was also recorded in the dry and rainy seasons.Monthly litterfall varied from 33.2(in the rainy season)to 87.6 g m^(-2) in the dry season,while leaf area index increased slightly in the rainy season.Climatic seasonality had no effect on concentrations of nitrogen,calcium,and magnesium,whereas phosphorous and potassium responded to rainfall seasonality oppositely.While phosphorous increased,potassium decreased during the dry season.Over seasons,nitrogen,potassium,and phosphorous decreased in leaf litter;calcium increased in leaf litter,while magnesium remained unaffected with leaf aging.Regardless,the five nutrients had similar remobilization rates over the year.The absence of climate seasonality on nutrient remobilization suggests that the current length of the dry season does not alter nutrient remobilization rates but this may change as dry periods become more prolonged in the future due to climate change.

Humic Acid Effects on Reducing Corn Leaf Burn Caused by Foliar Spray of Urea-Ammonium Nitrate at Different Humic Acid/Urea-Ammonium Nitrate Ratios

Technologies for reducing corn leaf burn caused by foliar spray of urea-ammonium nitrate (UAN) during the early growing season are limited. A field experiment was carried out to evaluate the effects of humic acid on corn leaf burn caused by foliar spray of undiluted UAN solution on corn canopy at Jackson, TN in 2018. Thirteen treatments of the mixtures of UAN and humic acid were evaluated at V6 of corn with different UAN application rates and different UAN/humic acid ratios. Leaf burn during 1 2, 3, 4, 5, 6, 7, and 14 days after UAN foliar spray significantly differed between with or without humic acid addition. The addition of humic acid to UAN significantly reduced leaf burn at each UAN application rate (15, 25, and 35 gal/acre). The reduction of leaf burn was enhanced as the humic acid/UAN ratio went up from 10% to 30%. Leaf burn due to foliar application of UAN became severer with higher UAN rates. The linear regression of leaf burn 14 days after application with humic acid/UAN ratio was highly significant and negative. However, the linear regression of leaf burn 14 days after application with the UAN application rate was highly significant and positive. In conclusion, adding humic acid to foliar-applied UAN is beneficial for reducing corn leaf burn during the early growing season.

Comprehensive Study on the Influence of Evapotranspiration and Albedo on Surface Temperature Related to Changes in the Leaf Area Index

Many studies have investigated the influence of evapotranspiration and albedo and emphasize their separate effects but ignore their interactive influences by changing vegetation status in large amplitudes. This paper focuses on the comprehensive influence of evapotranspiration and albedo on surface temperature by changing the leaf area index （LAD between 30^-90~N. Two LAI datasets with seasonally different amplitudes of vegetation change between 30^-90~N were used in the simulations. Seasonal differences between the results of the simulations are compared, and the major findings are as follows. （1） The interactive effects of evapotranspiration and albedo on surface temperature were different over different regions during three seasons [March-April-May （MAM）, June-July-August （JJA）, and September-October-November （SON）], i.e., they were always the same over the southeastern United States during these three seasons but were opposite over most regions between 30°-90°N during JJA. （2） Either evapotranspiration or albedo tended to be dominant over different areas and during different seasons. For example, evapotranspiration dominated almost all regions between 30^-90~N during JJA, whereas albedo played a dominant role over northwestern Eurasia during MAM and over central Eurasia during SON. （3） The response of evapotranspiration and albedo to an increase in LAI with different ranges showed different paces and signals. With relatively small amplitudes of increased LAI, the rate of the relative increase in evapotranspiration was quick, and positive changes happened in albedo. But both relative changes in evapotranspiration and albedo tended to be gentle, and the ratio of negative changes of albedo increased with relatively large increased amplitudes of LAI.

Direct measurement of the three-dimensional distribution of leaf area density and light conditions in a mature oak stand by the cube method

Although the distributions of foliage and light play major roles in various forest functions,accurate,nondestructive measurement of these distributions is difficult due to the complexity of the canopy structure.To evaluate the foliage and light distributions directly and nondestructively in a mature oak stand,we used the cube method by dividing the forest canopy into small cubes(50 cm per side)and directly measured leaf area density(LAD,the total one-sided leaf area per unit volume,i.e.,cube)and relative irradiance(RI)within each cube.The distribution of LAD and of RI was highly heterogeneous,even at the same canopy height.This heterogeneity reflected the presence of foliage clusters associated with multiple forking branches.The relationship between cumulative LAD at the canopy surface and average RI followed the Beer-Lambert law.The mean light extinction coefficient(K)was 0.32.However,K was overestimated by more than double(0.80)when calculated based on the classical method using RI at the forest floor.This overestimation was caused by the lower RI due to light absorption by nonleaf plant parts below the canopy.Our findings on the complex foliage and light distributions in canopy layers should help improve the accuracy of RI and K measurements and thus more accurate predictions of environmental responses and forest functions.

A Computer Program for Automatic Watering Based on Potential Evapotranspiration by Penman Method and Predicted Leaf Area in Miniature Pot Rose Production

In this study, we developed a computer program for automatic prediction of watering time point by considering the environmental factors such as solar radiation, air temperature and relative humidity based on the multiple linear regression equation of leaf area and Penman Method. The experiments were carried out for a year in two watering experimental plots, one of which was controlled by pF value, and the other by the computer program. After comparing the results of the two plots, the following findings were obtained. In the computer program plot, the observed and predicted values of both leaf area and evapotranspiration indicated significant correlation at the 1% level, which suggested that the computer program had high prediction accuracy. In addition, no significant difference was observed between the two experimental plots with respects to the plant height, plant diameter, leaf area, leaf number, fresh weight, and dry weight, which demonstrated that the plants in the computer program plot had normal growth. On the other hand, although the number of flower buds and flowering shoots showed higher values at the end of certain cultivations in the computer program plot than those in pF value plot, we proposed that it was due to the effect of cumulative daily solar radiation in the greenhouse, rather than the watering. Thus, we have reached the conclusion that the computer program for automatic prediction of watering time point developed by this study has high applicability in miniature pot rose production.

Optimization of Green Space Plant Configuration in Residential Areas of Chongqing Central Business District Based on Green Plot Ratio—A Case Study of Xuhui City Residential Community

The current urban green space construction was guided by a two-dimensional index evaluation system, resulting in weak ecological benefits of green space. Green plot ratio (GPR), as a three-dimensional indicator, can characterize the ecological benefits of green areas and the ability of green areas to participate in the operation and regulation of urban ecosystems. As an important component of urban green space, the GPR index was added to the two-dimensional index evaluation system to optimize the green space, which can promote the development of low-carbon, healthy and ecological green space. Based on the research of 22 residential districts in the central city of Chongqing, the Leaf area index (LAI) index of common native garden plants in Chongqing was formed to improve the accuracy of green capacity index measurement in Chongqing. The study also took the residential community of Sunrise City in Banan District of Chongqing as an example, and carried out the optimization design practice from four types of residential community green areas: green areas next to houses, road green areas, concentrated green areas, and green areas attached to public service facilities.

Identified the hydrochemical and the sulfur cycle process in subsidence area of Pingyu mining area using multi-isotopes combined with hydrochemistry methods

Groundwater serves as an important water source for residents in and around mining areas.To achieve scientific planning and efficient utilization of water resources in mining areas,it is essential to figure out the chemical formation process and the ground water sulfur cycle that transpire after the coal mining activities.Based on studies of hydrochemistry and D,^(18)O-H_(2)O,^(34)S-SO_(4)isotopes,this study applied principal component analysis,ion ratio and other methods in its attempts to reveal the hydrogeochemical action and sulfur cycle in the subsidence area of Pingyu mining area.The study discovered that,in the studied area,precipitation provides the major supply of groundwater and the main water chemistry effects are dominated by oxidation dissolution of sulfide minerals as well as the dissolution of carbonate and silicate rocks.The sulfate in groundwater primarily originates from oxidation and dissolution of sulfide minerals in coal-bearing strata and human activities.The mixed sulfate formed by the oxidation of sulfide minerals and by human activities continuously recharges the groundwater,promoting the dissolution of carbonate rock and silicate rock in the process.

Effects of leaf N concentration and leaf area index on determining rice tillering

Relative tillering rate(RTR)increased linear-ly with the increasing of leaf N concentration(NLV)has been already reported.To testwhether this relationship could be used toquantitatively explain the difference in tilleringamong a wide range of N application,field ex- periments were conducted at the IRRI farm,Los Banos,Laguna,the Philippines.Two in- dica cultivars,IR 72 and IR68284H wereused.For each cultivar,12 treatments includ- ing 4 N levels(0,60,120,and 180kgN·ha)and 3 transplanting spacing(30×20,20×20,and 10×20cm)were arranged in a ran-domized split-plot design with 4 replications.The N treatments were designated as mainplots and spacings as subplots.Fourteen-day-old seedlings were transplanted with 3seedlings per hill.The subplot area was 20m~2.Nitrogen fertilizer was applied as basal,atmidtillering,and at panicle initiation in threeequal splits.P,K,and Zn were applied asbasal at normal dosage.The field was flooded.Plant samples were taken every 7-14 d from 14d after transplanting to flower

New Vegetation Index and Its Application in Estimating Leaf Area Index of Rice

Leaf area index （LAI） is an important characteristic of land surface vegetation system, and is also a key parameter for the models of global water balancing and carbon circulation. By using the reflectance values of Landsat-5 blue, green and red channels simulated from rice reflectance spectrum, the sensitivities of the bands to LAI were analyzed, and the response and capability to estimate LAI of various NDVIs （normalized difference vegetation indices）, which were established by substituting the red band of general NDVI with all possible combinations of red, green and blue bands, were assessed. Finally, the conclusion was tested by rice data at different conditions. The sensitivities of red, green and blue bands to LAI were different under various conditions. When LAI was less than 3, red and blue bands were more sensitive to LAI. Though green band in the circumstances was less sensitive to LAI than red and blue bands, it was sensitive to LAI in a wider range. When the vegetation indices were constituted by all kinds of combinations of red, green and blue bands, the premise for making the sensitivity of these vegetation indices to LAI be meaningful was that the value of one of the combinations was greater than 0.024, i.e. visible reflectance （VIS）〉0.024. Otherwise, the vegetation indices would be saturated, resulting in lower estimation accuracy of LAI. Comparison on the capabilities of the vegetation indices derived from all kinds of combinations of red, green and blue bands to LAI estimation showed that GNDVI （Green NDVI） and GBNDVI （Green-Blue NDVI） had the best relations with LAI. The capabilities of GNDVI and GBNDVI to LAI estimation were tested under different circumstances, and the same result was acquired. It suggested that GNDVI and GBNDVI performed better to predict LAI than the conventional NDVI.

Comparative analysis of GF-1,HJ-1,and Landsat-8 data for estimating the leaf area index of winter wheat

Using simultaneously collected remote sensing data and field measurements, this study firstly assessed the consistency and applicability of China high-resolution earth observation system satellite 1 （GF-1） wide field of view （WFV） camera, environment and disaster monitoring and forecasting satellite （H J-l） charge coupled device （CCD）, and Landsat-8 opera- tional land imager （OLI） data for estimating the leaf area index （LAI） of winter wheat via reflectance and vegetation indices （VIs）. The accuracies of these LAI estimates were then assessed through comparison with an empirical model and the PROSAIL radiative transfer model. The effects of radiation calibration, spectral response functions, and spatial resolution on discrepancies in the LAI estimates between the different sensors were also analyzed. The results yielded the following observations： （1） The correlation between reflectance from different sensors is relative good, with the adjusted coefficients of determination （R2） between 0.375 to 0.818. The differences in reflectance are ranging from 0.002 to 0.054. The correlation between VIs from different sensors is high with the R2 between 0.729 and 0.933. The differences in the VIs are ranging from 0.07 to 0.156. These results show the three sensors＇ images can all be used for cross calibration of the reflectance and VIs. （2） The four VIs from the three sensors are all demonstrated to be highly correlated with LAI （R2 between 0.703 and 0.849）. The linear models associated with the 2-band enhanced vegetation index （EVI2）, which feature the highest R2 （higher than 0.746） and the lowest root mean square errors （RMSE） （less than 0.21）, were selected to estimate the winter wheat LAI. The accuracy of the estimated LAI from Landsat-8 was the highest, with the relative errors （RE） of 2.18% and an RMSE of 0.13, while the H J-1 was the lowest, with the RE of 2.43% and the RMSE of 0.15. （3） The inversion errors in the different sensors＇ LAI estimates using the PROSAIL model are small. The accuracy of the GF-1 is the highest with the RE of 3.44%, and the RMSE of 0.22, whereas that of the H J-1 is the lowest with the RE of 4.95%, and the RMSE of 0.26. （4） The effects of the spectral response function and radiation calibration for the different sensors are small and can be ignored, but the effects of spatial resolution are significant and must be taken into consideration in practical applications.

Determination of critical nitrogen dilution curve based on leaf area index for winter wheat in the Guanzhong Plain, Northwest China

Excessive use of nitrogen (N) fertilizers in agricultural systems increases the cost of production and risk of environmental pollution. Therefore, determination of optimum N requirements for plant growth is necessary. Previous studies mostly established critical N dilution curves based on aboveground dry matter (DM) or leaf dry matter (LDM) and stem dry matter (SDM), to diagnose the N nutrition status of the whole plant. As these methods are time consuming, we investigated the more rapidly determined leaf area index (LAI) method to establish the critical nitrogen (Nc) dilution curve, and the curve was used to diagnose plant N status for winter wheat in Guanzhong Plain in Northwest China. Field experiments were conducted using four N fertilization levels (0, 105, 210 and 315 kg ha?1) applied to six wheat cultivars in the 2013–2014 and 2014–2015 growing seasons. LAI, DM, plant N concentration (PNC) and grain yield were determined. Data points from four cultivars were used for establishing the Nc curve and data points from the remaining two cultivars were used for validating the curve. The Nc dilution curve was validated for N-limiting and non-N-limiting growth conditions and there was good agreement between estimated and observed values. The N nutrition index (NNI) ranged from 0.41 to 1.25 and the accumulated plant N deficit (Nand) ranged from 60.38 to –17.92 kg ha?1 during the growing season. The relative grain yield was significantly affected by NNI and was adequately described with a parabolic function. The Nc curve based on LAI can be adopted as an alternative and more rapid approach to diagnose plant N status to support N fertilization decisions during the vegetative growth of winter wheat in Guanzhong Plain in Northwest China.

Basal internode elongation of rice as affected by light intensity and leaf area

Short basal internodes are important for lodging resistance of rice(Oryza sativa L.).Several canopy indices affect the elongation of basal internodes,but uncertainty as to the key factors determining elongation of basal internodes persists.The objectives of this study were(1)to identify key factors affecting the elongation of basal internodes and(2)to establish a quantitative relationship between basal internode length and canopy indices.An inbred rice cultivar,Yinjingruanzhan,was grown in two split-plot field experiments with three N rates(0,75,and 150 kg N ha−1 in early season and 0,90,and 180 kg N ha−1 in late season)as main plots,three seedling densities(16.7,75.0,and 187.5 seedlings m−2)as subplots,and three replications in the 2015 early and late seasons in Guangzhou,China.Light intensity at base of canopy(Lb),light quality as determined from red/far-red light ratio(R/FR),light transmission ratio(LTR),leaf area index(LAI),leaf N concentration(NLV)and final length of second internode(counted from soil surface upward)(FIL)were recorded.Higher N rate and seedling density resulted in significantly longer FIL.FIL was negatively correlated with Lb,LTR,and R/FR(P<0.01)and positively correlated with LAI(P<0.01),but not correlated with NLV(P>0.05).Stepwise linear regression analysis showed that FIL was strongly associated with Lb and LAI(R2=0.82).Heavy N application to pot-grown rice at the beginning of first internode elongation did not change FIL.We conclude that FIL is determined mainly by Lb and LAI at jointing stage.NLV has no direct effect on the elongation of basal internodes.N application indirectly affects FIL by changing LAI and light conditions in the rice canopy.Reducing LAI and improving canopy light transmission at jointing stage can shorten the basal internodes and increase the lodging resistance of rice.

Mapping Spatial and Temporal Variations of Leaf Area Index for Winter Wheat in North China

Leaf area index （LAI） is an important parameter in a number of models related to ecosystem functioning, carbon budgets, climate, hydrology, and crop growth simulation. Mapping and monitoring the spatial and temporal variations of LAI are necessary for understanding crop growth and development at regional level. In this study, the relationships between LAI of winter wheat and Landsat TM spectral vegetation indices （SVIs） were analyzed by using the curve estimation procedure in North China Plain. The series of LAI maps retrieved by the best regression model were used to assess the spatial and temporal variations of winter wheat LAI. The results indicated that the general relationships between LAI and SVIs were curvilinear, and that the exponential model gave a better fit than the linear model or other nonlinear models for most SVIs. The best regression model was constructed using an exponential model between surface-reflectance-derived difference vegetation index （DVI） and LAI, with the adjusted R2 （0.82） and the RMSE （0.77）. The TM LAI maps retrieved from DVILAI model showed the significant spatial and temporal variations. The mean TM LAI value （30 m） for winter wheat of the study area increased from 1.29 （March 7, 2004） to 3.43 （April 8, 2004）, with standard deviations of 0.22 and 1.17, respectively. In conclusion, spectral vegetation indices from multi-temporal Landsat TM images can be used to produce fine-resolution LAI maps for winter wheat in North China Plain.

Simulation of leaf area index and biomass at landscape scale

The method for simulating the temporal and spatial distribution patterns of leaf area index (LAI) and biomass at landscape scale using remote sensing images and surface data was discussed in this paper. The procedure was: (1) annual maximum normalized difference vegetation index (NDVI) over the landscape was calculated from TM images; (2) the relationship model between NDVI and LAI was built and annual maximum LAI over the landscape was simulated; (3) the relationship models between LAI and biomass were built and annual branch, stem, root and maximum leaf biomass over the landscape were simulated; (4) spatial distribution patterns of leaf biomass and LAI in different periods all the year round were obtained. The simulation was based on spatial analysis module GRID in ArcInfo software. The method is also a kind of scaling method from patch scale to landscape scale. A case study of Changbai Mountain Nature Reserve was dissertated. Analysis and primary validation were carried out to the simulated LAI and biomass for the major vegetation types in the Changbai Mountain in 1995.

Leaf area index retrieval based on canopy reflectance and vegetation index in eastern China

The aim of this paper is to investigate the feasibility of using Landsat TM data to retrieve leaf area index (LAI). To get a LAI retrieval model based ground reflectance and vegetation index, detailed field data were collected in the study area of eastern China, dominated by bamboo, tea plant and greengage. Plant canopy reflectance of Landsat TM wavelength bands has been inversed using software of 6S. LAI is an important ecological parameter. In this paper, atmospheric corrected Landsat TM imagery was utilized to calculate different vegetation indices (VI), such as simple ratio vegetation index (SR), shortwave infrared modified simple ratio (MSR), and normalized difference vegetation index (NDVI). Data of 53 samples of LAI were measured by LAI-2000 (LI-COR) in the study area. LAI was modeled based on different reflectances of bands and different vegetation indices from Landsat TM and LAI samples data. There are certainly correlations between LAI and the reflectance of TM3, TM4, TM5 and TM7. The best model through analyzing the results is LAI = 1.2097*MSR + 0.4741 using the method of regression analysis. The result shows that the correlation coefficient R2 is 0.5157, and average accuracy is 85.75%. However, whether the model of this paper is suitable for application in subtropics needs to be verified in the future.

A NEW QUANTITATIVE WAY FOR DETERMINING LEAF AREA INDEXAND NET PRIMARY PRODUCTIVITY IN REGIONAL SCALE

An inversion of bidirectional reflection distribution fiJnedon (BRDF) wastested using NK Model and NOAA AVHRR datu. The test involVed sensitiveanalysis, optimum inversion selecting, ground simulated expenment, calibrahngmeasuremed with satellite and computer image processmg. Results of comparisonwith NDVI indicatal that inversion of BRDF will have brigh developing prospect inthe next decade.

Assimilation of temporal-spatial leaf area index into the CERES-Wheat model with ensemble Kalman filter and uncertainty assessment for improving winter wheat yield estimation

To accurately estimate winter wheat yields and analyze the uncertainty in crop model data assimilations, winter wheat yield estimates were obtained by assimilating measured or remotely sensed leaf area index （LAI） values. The performances of the calibrated crop environment resource synthesis for wheat （CERES-Wheat） model for two different assimilation scenarios were compared by employing ensemble Kalman filter （EnKF）-based strategies. The uncertainty factors of the crop model data assimilation was analyzed by considering the observation errors, assimilation stages and temporal-spatial scales. Overalll the results indicated a better yield estimate performance when the EnKF-based strategy was used to comprehen- sively consider several factors in the initial conditions and observations. When using this strategy, an adjusted coefficients of determination （R2） of 0.84, a root mean square error （RMSE） of 323 kg ha-1, and a relative errors （RE） of 4.15% were obtained at the field plot scale and an R2 of 0.81, an RMSE of 362 kg ha-1, and an RE of 4.52% were obtained at the pixel scale of 30 mx30 m. With increasing observation errors, the accuracy of the yield estimates obviously decreased, but an acceptable estimate was observed when the observation errors were within 20%. Winter wheat yield estimates could be improved significantly by assimilating observations from the middle to the end of the crop growing seasons. With decreasing assimilation frequency and pixel resolution, the accuracy of the crop yield estimates decreased; however, the computation time decreased. It is important to consider reasonable temporal-spatial scales and assimilation stages to obtain tradeoffs between accuracy and computation time, especially in operational systems used for regional crop yield estimates.

Varietal Difference in Leaf Nitrogen Content and Leaf Area and Their Effects to Ripening Rate During Mature Period of japonica Rice

Employing the pot experiment of the complete random block design with 6 replications,four varieties of japonica rice (Fujisaka 5,Honenwase,Akitakomachi and Taichung 65) were used to study the varietal differences in leaf nitrogen content(LNC) and leaf area during mature period,their relation and effects to the ripening rate.The results showed that(1) thee were varietal differences in LNC at the heading stage and the LNC decrease rate during the matue period,the high LNC at the heading stage was related to the rapid LNC decrease.(2) There were two phases of the leaf area changing process during the mature period,first was the stable,and second was the decreased phase.There was varietal difference in the critical time of phase 1 and phase 2.The hign leaf area in the phase 1 was in relation to the rapid leaf area decrease in the phase 2.It was not found that there was relation between the leaf quality and quantity.(3)It wa unfavorable to the ripening rate for the high leaf area at the heading stage and the rapid decrease of the leaf area during the mature period.(4)It was put forward that the super high yield rice variety should possess the not very high leaf area and high LNC at the heading stage,slow senescence in the leaf area during the mature period.

Performance and Analysis of a Model for Describing Layered Leaf Area Index of Rice

Layered leaf area index （LAIk） is one of the major determinants for rice canopy. The objective of this study is to attain rice LAI k using morphological traits especially leaf traits that affected plant type. A theoretical model based on rice geometrical structure was established to describe LAI k of rice with leaf length （Li）, width （Wi）, angle （Ai）, and space （Si）, and plant pole height （H） at booting and heading stages. In correlation with traditional manual measurement, the model was performed by high R2-values （0.95-0.89, n=24） for four rice hybrids （Liangyoupeijiu, Liangyou E32, Liangyou Y06, and Shanyou 63） with various plant types and four densities （3 750, 2 812, 1 875, and 1 125 plants per 100 m2） of a particular hybrid （Liangyoupeijiu）. The analysis of leaf length, width, angle, and space on LAI k for two hybrids （Liangyoupeijiu and Shanyou 63） showed that leaves length and space exhibited greater effects on the change of rice LAI k . The radiation intensity showed a significantly negative exponential relation to the accumulation of LAI k , which agreed to the coefficient of light extinction （K）. Our results suggest that plant type regulates radiation distribution through changing LAI k . The present model would be helpful to acquire leaf distribution and judge canopy structure of rice field by computer system after a simple and less-invasive measurement of leaf length, width, angle （by photo）, and space at field with non-dilapidation of plants.

DISTRIBUTION PATTERNS OF LEAF AREA INDEX FOR MAJOR CONIFEROUS FOREST TYPES IN CHINA

Leaf area index (LAI) of natural vegetation is recognized as the most important variable for measuring vegetation structure over large areas, and for relating it to energy and mass exchange, which has been successfully estimated from satellite resolution sensors. In this paper, according to the statistical analysis based on a lot of forest plots, the mathematical models of LAI distribution patterns in the hydro thermal spaces for five coniferous forest types in China were established. For the cold temperate larch forests growing in the dry and cold climate, their LAI increases with the increasing of warm index and precipitation in the way of hyperbolic quadratic surface. For the cold temperate spruce fir forests and temperate Pinus tabulaeformis forests, their LAI is negatively related to the annual mean air temperature in the way of the natural exponential curve, in order to adapt to the water oppressed environments. For the subtropical Pinus massoniana forests and Cunninghamia lanceolata forests growing in the warm and moist climate, their LAI is related to the annual mean air temperature in the way of the parabolic quadratic curve.