CN106991412A - A kind of method for obtaining round-the-clock effective soil moisture - Google Patents

A kind of method for obtaining round-the-clock effective soil moisture Download PDF

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CN106991412A
CN106991412A CN201710256966.5A CN201710256966A CN106991412A CN 106991412 A CN106991412 A CN 106991412A CN 201710256966 A CN201710256966 A CN 201710256966A CN 106991412 A CN106991412 A CN 106991412A
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冷佩
李召良
宋小宁
段四波
高懋芳
霍红元
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Abstract

The invention discloses a kind of method for obtaining round-the-clock effective soil moisture, comprise the following steps:Gather CLDAS meteorological datas;MODIS data are gathered, is pre-processed using ENVI softwares, is finally output as tiff forms;To MODIS as cloud differentiates, being divided into the cloudless pixels of MODIS and MODIS has cloud pixel, and carrying out the estimation cloudless pixels of MODIS and MODIS based on CLDAS meteorological datas and MODIS data has effective soil moisture of cloud pixel.This hair on the basis of the effective soil moisture of existing remote-sensing inversion, for have cloud pixel can not the normal effective soil moisture of inverting situation, the method for proposing to be estimated using meteorological data information obtains round-the-clock effective soil moisture data so as to realize.

Description

一种获取全天候有效土壤水分的方法A method of obtaining available soil moisture around the clock

技术领域technical field

本发明属于定量遥感技术领域,具体地说,涉及一种获取全天候有效土壤水分的方法。The invention belongs to the technical field of quantitative remote sensing, and in particular relates to a method for obtaining all-weather effective soil moisture.

背景技术Background technique

有效土壤水分是土壤中能够被作物所利用的水分,它对于作物生长非常重要,也是进行干旱监测的重要指标。在区域尺度中,通常利用光学与热红外遥感技术来获取区域连续的有效土壤水分。然而,当遇到雨云等不利天气条件时,光学与热红外像元可能无法获取有效的观测值,导致遥感方法反演失效,从而无法获得全天候的有效土壤水分。对此,本发明充分挖掘气象数据的潜力,利用现有全天候气象数据产品信息弥补遥感数据缺失给全天候有效土壤水分反演带来的不便,提出一种获取全天候有效土壤水分的方法,为指导农业生产活动和作物生长提供可靠的土壤水分信息,就有重要的应用价值和实际意义。Effective soil moisture is the water in the soil that can be used by crops. It is very important for crop growth and is also an important indicator for drought monitoring. On a regional scale, optical and thermal infrared remote sensing techniques are usually used to obtain regional continuous effective soil moisture. However, when encountering unfavorable weather conditions such as rain clouds, optical and thermal infrared pixels may not be able to obtain effective observation values, resulting in the inversion of remote sensing methods to fail, so that it is impossible to obtain effective soil moisture around the clock. In this regard, the present invention fully taps the potential of meteorological data, uses the existing all-weather meteorological data product information to make up for the inconvenience caused by the lack of remote sensing data to the all-weather effective soil moisture inversion, and proposes a method for obtaining all-weather effective soil moisture. Production activities and crop growth provide reliable soil moisture information, which has important application value and practical significance.

传统的区域有效土壤水分一般利用光学与热红外遥感技术获取,只能在晴空条件下使用,对于非晴空像元,一般无法获取有效的观测值,从而无法反演全天候有效土壤水分。Traditional regional effective soil moisture is generally obtained by optical and thermal infrared remote sensing technology, which can only be used under clear sky conditions. For non-clear sky pixels, it is generally impossible to obtain effective observation values, so it is impossible to retrieve all-weather effective soil moisture.

发明内容Contents of the invention

有鉴于此,本发明针对现有光学与热红外遥感技术中存在的非晴空像元不能够直接获取有效土壤水分的问题,提供了一种获取全天候有效土壤水分的方法,从而实现全天候有效土壤水分的获取。In view of this, the present invention provides a method for obtaining all-weather effective soil moisture for the problem that the non-clear sky pixel in the existing optical and thermal infrared remote sensing technology cannot directly obtain effective soil moisture, so as to realize all-weather effective soil moisture of acquisition.

为了解决上述技术问题,本发明公开了一种获取全天候有效土壤水分的方法,包括以下步骤:In order to solve the above technical problems, the present invention discloses a method for obtaining all-weather effective soil moisture, comprising the following steps:

步骤1、采集CLDAS气象数据:CLDAS气象数据包括气温、风速、短波辐射和比湿;Step 1. Collect CLDAS meteorological data: CLDAS meteorological data include air temperature, wind speed, shortwave radiation and specific humidity;

步骤2、采集MODIS数据,利用ENVI软件进行预处理,最后输出为tiff格式,作为本发明的输入数据:MODIS数据包括地表温度产品、8天合成的叶面积指数产品以及16天合成归一化植被指数产品;Step 2, collect MODIS data, utilize ENVI software to carry out preprocessing, finally output is tiff format, as the input data of the present invention: MODIS data comprises the leaf area index product of surface temperature product, 8 days synthesis and 16 days synthesis normalized vegetation index products;

步骤3、对MODIS像云进行判别,分为MODIS无云像元与MODIS有云像元,基于CLDAS气象数据和MODIS数据进行估算MODIS无云像元和MODIS有云像元的有效土壤水分。Step 3. Discriminate the MODIS image cloud, divide it into MODIS cloudless pixel and MODIS cloudy pixel, and estimate the effective soil moisture of MODIS cloudless pixel and MODIS cloudy pixel based on CLDAS meteorological data and MODIS data.

进一步地,MODIS无云像元与MODIS有云像元是MODIS产品数据自带的属性,只要下载数据后就能直观获得此信息。Furthermore, MODIS cloudless pixels and MODIS cloudy pixels are the attributes of MODIS product data, and this information can be obtained directly after downloading the data.

进一步地,步骤3中的估算MODIS无云像元的有效土壤水分具体为:Further, the estimated effective soil moisture of MODIS cloud-free pixel in step 3 is specifically:

计算干燥裸土温度Ts,max,湿润裸土温度Ts,min,受水分胁迫的全植被覆盖温度Tc,max和水分状况良好的全植被覆盖温度Tc,min四个温度值,计算公式分别为:Calculate the four temperature values of dry bare soil temperature T s,max , wet bare soil temperature T s,min , full vegetation coverage temperature T c,max under water stress and full vegetation coverage temperature T c,min with good water conditions, and calculate The formulas are:

其中,Δ是饱和水汽压随温度变化的斜率,表示为气温的函数;Among them, Δ is the slope of the saturated water vapor pressure with temperature, expressed as a function of air temperature;

其中,Ta是气温,从CLDAS数据中读取; where T a is the air temperature, read from the CLDAS data;

Cv是空气比热,取值为1295.16;C v is the specific heat of air, the value is 1295.16;

rcx和rcp分别是最大冠层阻抗和潜在蒸发时的冠层阻抗,rcx取值为2000,rcp根据LAI进行计算,rcp=100/LAI,其中,LAI从MODIS数据中读取;r cx and r cp are the maximum canopy impedance and the canopy impedance of potential evaporation respectively, the value of r cx is 2000, r cp is calculated according to LAI, r cp =100/LAI, where LAI is read from MODIS data ;

γ是干湿表常数(取值0.066);γ is the psychrometer constant (value 0.066);

VPD是饱和水汽压差,利用CLDAS的气温和比湿数据进行计算;VPD is the saturated water vapor pressure difference, calculated using the air temperature and specific humidity data of CLDAS;

Rn是净辐射,利用CLDAS数据读取下行短波辐射(Sd)、气温(Ta)以及四个极端条件下的反照率进行计算;Rn=(1-αs)SdsεaσTa 4sσTa 4其中,αs是地表反照率,在干燥裸土、湿润裸土、受水分胁迫的全植被覆,盖和水分良好的全植被覆盖条件下分别取值为0.20,0.10,0.25和0.15;εs为地表比辐射率,干燥和湿润的裸土条件分别为0.96和0.97,受水分胁迫的全植被和水分良好的全植被分别为0.975和0.985;σ是Stefan-Boltzmann常数,5.67×10-8;εa是天空发射率,表示为气温的函数εa=9.2×10-6×Ta 2R n is the net radiation, which is calculated by reading the downgoing shortwave radiation (S d ), air temperature (T a ) and albedo under four extreme conditions using CLDAS data; R n = (1-α s ) S ds ε a σT a 4s σT a 4 Among them, α s is the surface albedo, which is taken under the conditions of dry bare soil, wet bare soil, full vegetation coverage under water stress, and full vegetation coverage with good water are 0.20, 0.10, 0.25 and 0.15; ε s is the specific emissivity of the surface, which is 0.96 and 0.97 for dry and wet bare soil conditions, and 0.975 and 0.985 for water-stressed and well-watered vegetation; σ is Stefan-Boltzmann constant, 5.67×10 -8 ; ε a is the emissivity of the sky, expressed as a function of air temperature ε a =9.2×10 -6 ×T a 2 ;

G是土壤热通量,表示为Rn的函数;G=[0.05+0.265×(1-FVC)]Rn,其中,FVC是植被覆盖度,利用归一化植被指数(NDVI)产品(MOD13A2)计算:G is the soil heat flux, expressed as a function of R n ; G=[0.05+0.265×(1-FVC)]R n , where FVC is the vegetation coverage, using the normalized difference vegetation index (NDVI) product (MOD13A2 )calculate:

其中,NDVI直接从MODIS数据中读取,NDVImax和NDVImin分别对应全植被覆盖和裸土的NDVI,从MOD13A2数据中得到,或者根据经验公式得到,分别给定为0.86和0.2;Among them, NDVI is directly read from the MODIS data, NDVI max and NDVI min correspond to the NDVI of full vegetation coverage and bare soil, respectively, and are obtained from MOD13A2 data, or according to empirical formulas, and are given as 0.86 and 0.2, respectively;

ra是空气动力学粗糙度,计算公式为:r a is the aerodynamic roughness, the calculation formula is:

其中,Z0M和Z0H分别是动量传输和能量传输粗糙度长度,d是零平面位移,z0是表面粗糙长度,u2是2m处风速;设植被高度为h,则d=0.65h,z0=0.1h,Z0M=0.1h,Z0H=0.1Z0M;2m处风速u2由CLDAS数据的10m处风速U进行换算,计算公式为:Among them, Z 0M and Z 0H are the roughness lengths of momentum transmission and energy transmission respectively, d is the zero plane displacement, z 0 is the surface roughness length, u 2 is the wind speed at 2m; if the vegetation height is h, then d=0.65h, z 0 =0.1h, Z 0M =0.1h, Z 0H =0.1Z 0M ; the wind speed u 2 at 2m is converted from the wind speed U at 10m from CLDAS data, and the calculation formula is:

对于MODIS无云像元,有效土壤水分的计算公式为:For MODIS cloudless pixels, the calculation formula of effective soil moisture is:

其中,Ts是直接从MODIS的温度产品中读取的数据。where Ts is the data read directly from the MODIS temperature product.

进一步地,步骤3中的估算MODIS有云像元的有效土壤水分具体为:Further, the estimated effective soil moisture of MODIS cloudy pixel in step 3 is specifically:

计算地表阻抗:Calculate the ground impedance:

其中,us是地表粗糙度影响最小的高度处的风速,利用叶面积指数,叶子直径和植被高度进行估算,设植被高度为h,叶子直径为s,则us近似为:Among them, u s is the wind speed at the height where the influence of surface roughness is the smallest. It is estimated by using the leaf area index, leaf diameter and vegetation height. Assuming that the vegetation height is h and the leaf diameter is s, then u s is approximated as:

其中,LAI是叶面积指数,从MODIS数据直接读取;Among them, LAI is the leaf area index, read directly from the MODIS data;

MODIS有云像元有效土壤水分M0近似计算为:The approximate calculation of the effective soil moisture M0 of the cloudy pixel in MODIS is :

与现有技术相比,本发明可以获得包括以下技术效果:Compared with prior art, the present invention can obtain and comprise following technical effect:

1)本发在现有遥感反演有效土壤水分的基础上,针对有云像元无法正常反演有效土壤水分的情况,提出利用气象数据信息进行估算的方法,弥补了单纯使用遥感方法在有云条件下无法反演有效土壤水分的缺陷。1) On the basis of the existing remote sensing inversion of effective soil moisture, this paper proposes a method for estimating using meteorological data information for the situation that cloudy pixels cannot normally invert the effective soil moisture, which makes up for the simple use of remote sensing methods in effective soil moisture. The deficiency of effective soil moisture cannot be retrieved under cloud conditions.

2)本发明融合遥感和气象数据信息,能够获取空间上连续的全天候有效土壤水分,为区域研究提供完整的土壤水分数据;2) The present invention integrates remote sensing and meteorological data information, can obtain spatially continuous all-weather effective soil moisture, and provides complete soil moisture data for regional research;

3)本发明满足了定量遥感领域研究对地面数据信息完整性的需求。3) The present invention satisfies the requirement for the integrity of ground data information in the field of quantitative remote sensing.

当然,实施本发明的任一产品并不一定需要同时达到以上所述的所有技术效果。Of course, implementing any product of the present invention does not necessarily need to achieve all the technical effects described above at the same time.

附图说明Description of drawings

此处所说明的附图用来提供对本发明的进一步理解,构成本发明的一部分,本发明的示意性实施例及其说明用于解释本发明,并不构成对本发明的不当限定。在附图中:The accompanying drawings described here are used to provide a further understanding of the present invention, and constitute a part of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention, and do not constitute improper limitations to the present invention. In the attached picture:

图1是本发明获取全天候有效土壤水分的方法的流程图;Fig. 1 is the flowchart of the method that the present invention obtains all-weather effective soil moisture;

图2是本发明2015年9月20日河南省MODIS地表温度;Fig. 2 is the MODIS surface temperature of Henan Province on September 20, 2015 of the present invention;

图3是本发明2015年9月20日河南省MODIS归一化植被指数(NDVI);Fig. 3 is the Henan province MODIS normalized difference vegetation index (NDVI) on September 20, 2015 of the present invention;

图4是本发明2015年9月20日河南省气象数据,其中,(a)为比湿,(b)为风速;Fig. 4 is the meteorological data of Henan Province on September 20, 2015 of the present invention, wherein, (a) is specific humidity, and (b) is wind speed;

图5是2015年9月20日河南省有效土壤水分,其中,(a)为传统遥感反演方法,(b)为本发明的方法。Figure 5 shows the effective soil moisture in Henan Province on September 20, 2015, where (a) is the traditional remote sensing inversion method, and (b) is the method of the present invention.

具体实施方式detailed description

以下将配合实施例来详细说明本发明的实施方式,藉此对本发明如何应用技术手段来解决技术问题并达成技术功效的实现过程能充分理解并据以实施。The implementation of the present invention will be described in detail below with examples, so as to fully understand and implement the implementation process of how the present invention uses technical means to solve technical problems and achieve technical effects.

本发明获取全天候有效土壤水分所需的数据为中国气象局陆面数据同化系统(China Meteorological Administration Land Data Assimilation System,CLDAS)实时气象数据和美国的MODIS(Moderate Resolution Imaging Spectroradiometer)数据,无需其它辅助数据。The data required by the present invention to obtain all-weather effective soil moisture are the real-time meteorological data of the China Meteorological Administration Land Data Assimilation System (CLDAS) and the MODIS (Moderate Resolution Imaging Spectroradiometer) data of the United States, without other auxiliary data .

本发明提供一种获取全天候有效土壤水分的方法,如图1所示,包括以下步骤:The present invention provides a method for obtaining all-weather effective soil moisture, as shown in Figure 1, comprising the following steps:

步骤1:CLDAS气象数据:Step 1: CLDAS Meteorological Data:

从中国气象数据共享网下载CLDAS气象要素产品,包括气温、风速、短波辐射和比湿,下载网址为:http://data.cma.cn/data/detail/dataCode/NAFP_CLDAS_RT.html。无需进行任何预处理操作,可直接作为本发明的输入数据。Download the CLDAS meteorological element products from the China Meteorological Data Sharing Network, including temperature, wind speed, short-wave radiation and specific humidity. The download URL is: http://data.cma.cn/data/detail/dataCode/NAFP_CLDAS_RT.html. Without any preprocessing operation, it can be directly used as the input data of the present invention.

步骤2:MODIS数据Step 2: MODIS Data

从MODIS数据网站https://ladsweb.nascom.nasa.gov/search/下载产品数据,包括地表温度(LST)产品(MOD11A1)、8天合成的叶面积指数(LAI)产品(MOD15A2)以及16天合成归一化植被指数(NDVI)产品(MOD13A2)。利用ENVI软件进行预处理,主要包括:投影、拼接、裁剪等,最后输出为tiff格式,作为本发明的输入数据。Download product data from the MODIS data website https://ladsweb.nascom.nasa.gov/search/, including the Land Surface Temperature (LST) product (MOD11A1), the 8-day synthetic Leaf Area Index (LAI) product (MOD15A2), and the 16-day Synthetic Normalized Difference Vegetation Index (NDVI) product (MOD13A2). Utilize ENVI software to carry out preprocessing, mainly include: projecting, splicing, cropping etc., finally output is tiff format, as the input data of the present invention.

步骤3:估算MODIS像元有效土壤水分Step 3: Estimate MODIS Pixel Effective Soil Moisture

对MODIS像云进行判别,分为MODIS无云像元与MODIS有云像元,MODIS无云像云一般有正常的像元温度值,可以直接利用遥感数据反演有效土壤水分;MODIS有云像元则没有像元温度值,因而不能直接反演有效土壤水分。这是MODIS产品数据自带的属性,只要下载数据后就能直观获得此信息,无需额外方法和过程进行判断;本发明根据不同的情况进行处理:Distinguishing MODIS image cloud is divided into MODIS cloudless pixel and MODIS cloudy pixel. MODIS cloudless image cloud generally has a normal pixel temperature value, and remote sensing data can be directly used to retrieve effective soil moisture; MODIS cloud image There is no pixel temperature value, so the effective soil moisture cannot be directly retrieved. This is an attribute of the MODIS product data. As long as the data is downloaded, this information can be obtained intuitively, without additional methods and processes for judgment; the present invention handles it according to different situations:

(1)无云象元(1) Cloudless pixel

对于MODIS无云像元,首先计算四个温度值,即:干燥裸土温度Ts,max,湿润裸土温度Ts,min,受水分胁迫的全植被覆盖温度Tc,max和水分状况良好的全植被覆盖温度Tc,min,计算公式分别为:For MODIS cloudless pixels, first calculate four temperature values, namely: dry bare soil temperature T s,max , wet bare soil temperature T s,min , temperature of full vegetation coverage under water stress T c,max and good water condition The full vegetation coverage temperature T c,min , the calculation formulas are:

其中,Δ是饱和水汽压随温度变化的斜率,可以表示为气温的函数,其中,Ta是气温;Cv是空气比热(取值1295.16);rcx和rcp分别是最大冠层阻抗和潜在蒸发时的冠层阻抗,rcx可以给一定值(2000),rcp可以根据LAI进行计算(rcp=100/LAI),其中,LAI可以从MODIS数据中读取;γ是干湿表常数(取值0.066);Ta是气温,从CLDAS数据中读取;VPD是饱和水汽压差,可以利用CLDAS的气温和比湿数据进行计算;Rn是净辐射,利用CLDAS数据读取下行短波辐射(Sd)、Among them, Δ is the slope of the saturated water vapor pressure changing with temperature, which can be expressed as a function of air temperature, Among them, T a is the air temperature; C v is the air specific heat (1295.16); r cx and r cp are the maximum canopy impedance and the canopy impedance of potential evaporation, respectively, r cx can give a certain value (2000), r cp can be calculated according to LAI (r cp =100/LAI), where LAI can be read from MODIS data; γ is the psychrometer constant (value 0.066); T a is air temperature, read from CLDAS data; VPD is the saturated water vapor pressure difference, which can be calculated by using the air temperature and specific humidity data of CLDAS; R n is the net radiation, which can be read by using the CLDAS data to read the downgoing shortwave radiation (S d ),

气温(Ta)以及四个极端条件下的反照率进行计算,Rn=(1-αs)SdsεaσTa 4sσTa 4,其中,αs是地表反照率,在干燥裸土、湿润裸土、受水分胁迫的全植被覆盖和水分良好的全植被覆盖条件下分别取值为0.20,0.10,0.25和0.15。εs为地表比辐射率,干燥和湿润的裸土条件分别为0.96和0.97,受水分胁迫的全植被和水分良好的全植被分别为0.975和0.985。σ是Stefan-Boltzmann常数(5.67×10-8)。εa是天空发射率,表示为气温Air temperature (T a ) and albedo under four extreme conditions are calculated, R n = (1-α s )S ds ε a σT a 4s σT a 4 , where α s is the surface albedo The values are 0.20, 0.10, 0.25 and 0.15 under the conditions of dry bare soil, wet bare soil, full vegetation coverage under water stress and full vegetation coverage with good water, respectively. ε s is the surface specific emissivity, which is 0.96 and 0.97 for dry and wet bare soil conditions, and 0.975 and 0.985 for water-stressed whole vegetation and well-watered whole vegetation, respectively. σ is a Stefan-Boltzmann constant (5.67×10 -8 ). ε a is the sky emissivity expressed as air temperature

的函数εa=9.2×10-6×Ta 2。G是土壤热通量,可以表示为Rn的函数。G=[0.05+0.265×(1-FVC)]Rn,其中,FVC是植被覆盖度,可以利用归一化植被The function of ε a =9.2×10 -6 ×T a 2 . G is the soil heat flux, which can be expressed as a function of Rn . G=[0.05+0.265×(1-FVC)]R n , where FVC is the vegetation coverage, and the normalized vegetation can be used

指数(NDVI)产品(MOD13A2)计算: Index (NDVI) product (MOD13A2) calculation:

其中,NDVI可直接从MODIS数据中读取,NDVImax和NDVImin分别对应全植被覆盖和裸土的NDVI,可以从MOD13A2数据中得到,也可以根据经验公式,分别给定为0.86和0.2。Among them, NDVI can be read directly from MODIS data. NDVI max and NDVI min correspond to the NDVI of full vegetation coverage and bare soil, respectively, which can be obtained from MOD13A2 data, and can also be given as 0.86 and 0.2 according to empirical formulas.

ra是空气动力学粗糙度,计算公式为:r a is the aerodynamic roughness, the calculation formula is:

其中,Z0MZ0H分别是动量传输和能量传输粗糙度长度,d是零平面位移,z0是表面粗糙长度,u2是2m处风速。假设植被高度为h,则d=0.65h,z0=0.1h,Z0M=0.1h,Z0H=0.1Z0M;2m处风速u2由CLDAS数据的10m处风速U进行换算,计算公式为:Among them, Z0M and Z0H are the roughness lengths of momentum transfer and energy transfer respectively, d is the zero plane displacement, z0 is the surface roughness length, and u2 is the wind speed at 2m . Assuming that the vegetation height is h, then d=0.65h, z 0 =0.1h, Z 0M =0.1h, Z 0H =0.1Z 0M ; the wind speed u 2 at 2m is converted from the wind speed U at 10m from CLDAS data, and the calculation formula is :

对于MODIS无云像元,有效土壤水分的计算公式为:For MODIS cloudless pixels, the calculation formula of effective soil moisture is:

其中,Ts是直接从MODIS的温度产品中读取的数据。where Ts is the data read directly from the MODIS temperature product.

(2)有云象元(2) There are cloud pixels

对于有云像元,首先计算地表阻抗:For cloudy pixels, the ground surface impedance is calculated first:

其中,us是地表粗糙度影响最小的高度处的风速,可以利用叶面积指数,叶子直径和植被高度进行估算。假设植被高度为h,叶子直径为s,则us可以近似为:where u s is the wind speed at the height at which the influence of surface roughness is minimal, which can be estimated using leaf area index, leaf diameter, and vegetation height. Assuming that the vegetation height is h and the leaf diameter is s, u s can be approximated as:

其中,LAI是叶面积指数,可以从MODIS数据直接读取。Among them, LAI is the leaf area index, which can be read directly from MODIS data.

MODIS有云像元有效土壤水分M0可以近似计算为:The effective soil moisture M0 of MODIS cloudy pixel can be approximated as:

根据公式(8)和公式(11),分别可以计算有云像元和无云像元的有效土壤水分,从而实现全天候有效土壤水分的获取。According to formula (8) and formula (11), the effective soil moisture of cloudy pixel and cloudless pixel can be calculated respectively, so as to realize the acquisition of effective soil moisture all-weather.

实施例1Example 1

以河南省为研究区,图2是2015年9月20日河南省MODIS的地表温度,从图中可以看出河南北部、东部部分地区以及西部部分地区数据缺失,呈现大量空白区域;图3为归一化植被指数。这两个数据是本发明的直接输入数据。图4是本发明的另外一套直接输入数据,即CLDAS气象数据。Taking Henan Province as the research area, Figure 2 shows the MODIS surface temperature of Henan Province on September 20, 2015. It can be seen from the figure that the data in the northern, eastern and western parts of Henan Province are missing, showing a large number of blank areas; Figure 3 is Normalized Difference Vegetation Index. These two data are direct input data of the present invention. Fig. 4 is another set of direct input data of the present invention, namely CLDAS meteorological data.

图5是有效土壤水分反演结果。图5(a)是传统遥感方法反演的结果,图5(b)是本发明的方法。从两个图的对比可以看出,传统遥感反演方法在无有效MODIS像元值的情况下无法反演有效土壤水分,而本发明的方法能够弥补这一缺憾,实现有效土壤水分的全天候反演,且反演结果呈现良好的空间连续性。Figure 5 is the inversion result of effective soil moisture. Fig. 5(a) is the inversion result of the traditional remote sensing method, and Fig. 5(b) is the method of the present invention. It can be seen from the comparison of the two figures that the traditional remote sensing inversion method cannot invert the effective soil moisture without effective MODIS pixel values, but the method of the present invention can make up for this shortcoming and realize the all-weather inversion of effective soil moisture and the inversion results show good spatial continuity.

上述说明示出并描述了发明的若干优选实施例,但如前所述,应当理解发明并非局限于本文所披露的形式,不应看作是对其他实施例的排除,而可用于各种其他组合、修改和环境,并能够在本文所述发明构想范围内,通过上述教导或相关领域的技术或知识进行改动。而本领域人员所进行的改动和变化不脱离发明的精神和范围,则都应在发明所附权利要求的保护范围内。The above description shows and describes several preferred embodiments of the invention, but as previously stated, it should be understood that the invention is not limited to the form disclosed herein, and should not be regarded as excluding other embodiments, but can be used in various other embodiments. Combinations, modifications and circumstances, and can be modified within the scope of the inventive concept described herein, by the above teachings or by skill or knowledge in the relevant field. However, changes and changes made by those skilled in the art do not depart from the spirit and scope of the invention, and should be within the protection scope of the appended claims of the invention.

Claims (4)

1.一种获取全天候有效土壤水分的方法,其特征在于,包括以下步骤:1. a method for obtaining all-weather effective soil moisture, is characterized in that, comprises the following steps: 步骤1、采集CLDAS气象数据:CLDAS气象数据包括气温、风速、短波辐射和比湿;Step 1. Collect CLDAS meteorological data: CLDAS meteorological data include air temperature, wind speed, shortwave radiation and specific humidity; 步骤2、采集MODIS数据,利用ENVI软件进行预处理,最后输出为tiff格式,作为本发明的输入数据:MODIS数据包括地表温度产品、8天合成的叶面积指数产品以及16天合成归一化植被指数产品;Step 2, collect MODIS data, utilize ENVI software to carry out preprocessing, finally output is tiff format, as the input data of the present invention: MODIS data comprises the leaf area index product of surface temperature product, 8 days synthesis and 16 days synthesis normalized vegetation index products; 步骤3、对MODIS像云进行判别,分为MODIS无云像元与MODIS有云像元,基于CLDAS气象数据和MODIS数据进行估算MODIS无云像元和MODIS有云像元的有效土壤水分。Step 3. Discriminate the MODIS image cloud, divide it into MODIS cloudless pixel and MODIS cloudy pixel, and estimate the effective soil moisture of MODIS cloudless pixel and MODIS cloudy pixel based on CLDAS meteorological data and MODIS data. 2.根据权利要求1所述的获取全天候有效土壤水分的方法,其特征在于,MODIS无云像元与MODIS有云像元是MODIS产品数据自带的属性,只要下载数据后就能直观获得此信息。2. the method for obtaining all-weather effective soil moisture according to claim 1, characterized in that, MODIS cloudless pixel and MODIS cloudy pixel are the attributes of MODIS product data, as long as the data is downloaded, the data can be directly obtained information. 3.根据权利要求2所述的获取全天候有效土壤水分的方法,其特征在于,所述步骤3中的估算MODIS无云像元的有效土壤水分具体为:3. the method for obtaining all-weather effective soil moisture according to claim 2, is characterized in that, the effective soil moisture of the estimation MODIS cloudless pixel in described step 3 is specifically: 计算干燥裸土温度Ts,max,湿润裸土温度Ts,min,受水分胁迫的全植被覆盖温度Tc,max和水分状况良好的全植被覆盖温度Tc,min四个温度值,计算公式分别为:Calculate the four temperature values of dry bare soil temperature T s,max , wet bare soil temperature T s,min , full vegetation coverage temperature T c,max under water stress and full vegetation coverage temperature T c,min with good water conditions, and calculate The formulas are: TT sthe s ,, mm aa xx == [[ rr aa (( RR nno -- GG )) CC vv ]] ++ TT aa -- -- -- (( 11 )) TT sthe s ,, mm ii nno == [[ rr aa (( RR nno -- GG )) CC vv ]] ·&Center Dot; [[ γγ (( ΔΔ ++ γγ )) ]] -- VV PP DD. ΔΔ ++ γγ ++ TT aa -- -- -- (( 22 )) TT cc ,, mm aa xx == [[ rr aa (( RR nno -- GG )) CC vv ]] ·&Center Dot; [[ γγ (( 11 ++ rr cc xx rr aa )) ΔΔ ++ γγ (( 11 ++ rr cc xx rr aa )) ]] -- VV PP DD. ΔΔ ++ γγ (( 11 ++ rr cc xx rr aa )) ++ TT aa -- -- (( 33 )) TT cc ,, mm ii nno == [[ rr aa (( RR nno -- GG )) CC vv ]] ·&Center Dot; [[ γγ (( 11 ++ rr cc pp rr aa )) ΔΔ ++ γγ (( 11 ++ rr cc pp rr aa )) ]] -- VV PP DD. ΔΔ ++ γγ (( 11 ++ rr cc pp rr aa )) ++ TT aa -- -- -- (( 44 )) 其中,Δ是饱和水汽压随温度变化的斜率,表示为气温的函数;Among them, Δ is the slope of the saturated water vapor pressure with temperature, expressed as a function of air temperature; 其中,Ta是气温,从CLDAS数据中读取; where T a is the air temperature, read from the CLDAS data; Cv是空气比热,取值为1295.16;C v is the specific heat of air, the value is 1295.16; rcx和rcp分别是最大冠层阻抗和潜在蒸发时的冠层阻抗,rcx取值为2000,rcp根据LAI进行计算,rcp=100/LAI,其中,LAI从MODIS数据中读取;r cx and r cp are the maximum canopy impedance and the canopy impedance of potential evaporation respectively, the value of r cx is 2000, r cp is calculated according to LAI, r cp =100/LAI, where LAI is read from MODIS data ; γ是干湿表常数(取值0.066);γ is the psychrometer constant (value 0.066); VPD是饱和水汽压差,利用CLDAS的气温和比湿数据进行计算;VPD is the saturated water vapor pressure difference, calculated using the air temperature and specific humidity data of CLDAS; Rn是净辐射,利用CLDAS数据读取下行短波辐射(Sd)、气温(Ta)以及四个极端条件下的反照率进行计算;Rn=(1-αs)SdsεaσTa 4sσTa 4其中,αs是地表反照率,在干燥裸土、湿润裸土、受水分胁迫的全植被覆,盖和水分良好的全植被覆盖条件下分别取值为0.20,0.10,0.25和0.15;εs为地表比辐射率,干燥和湿润的裸土条件分别为0.96和0.97,受水分胁迫的全植被和水分良好的全植被分别为0.975和0.985;σ是Stefan-Boltzmann常数,5.67×10-8;εa是天空发射率,表示为气温的函数εa=9.2×10-6×Ta 2R n is the net radiation, which is calculated by reading the downgoing shortwave radiation (S d ), air temperature (T a ) and albedo under four extreme conditions using CLDAS data; R n = (1-α s ) S ds ε a σT a 4s σT a 4 Among them, α s is the surface albedo, which is taken under the conditions of dry bare soil, wet bare soil, full vegetation coverage under water stress, and full vegetation coverage with good water are 0.20, 0.10, 0.25 and 0.15; ε s is the specific emissivity of the surface, which is 0.96 and 0.97 for dry and wet bare soil conditions, and 0.975 and 0.985 for water-stressed and well-watered vegetation; σ is Stefan-Boltzmann constant, 5.67×10 -8 ; ε a is the emissivity of the sky, expressed as a function of air temperature ε a =9.2×10 -6 ×T a 2 ; G是土壤热通量,表示为Rn的函数;G=[0.05+0.265×(1-FVC)]Rn,其中,FVC是植被覆盖度,利用归一化植被指数(NDVI)产品(MOD13A2)计算:G is the soil heat flux, expressed as a function of R n ; G=[0.05+0.265×(1-FVC)]R n , where FVC is the vegetation coverage, using the normalized difference vegetation index (NDVI) product (MOD13A2 )calculate: Ff VV CC == [[ NN DD. VV II -- NDVINDVI minmin NDVINDVI mm aa xx -- NDVINDVI minmin ]] 22 -- -- -- (( 55 )) 其中,NDVI直接从MODIS数据中读取,NDVImax和NDVImin分别对应全植被覆盖和裸土的NDVI,从MOD13A2数据中得到,或者根据经验公式得到,分别给定为0.86和0.2;Among them, NDVI is directly read from the MODIS data, NDVI max and NDVI min correspond to the NDVI of full vegetation coverage and bare soil, respectively, and are obtained from MOD13A2 data, or according to empirical formulas, and are given as 0.86 and 0.2, respectively; ra是空气动力学粗糙度,计算公式为:r a is the aerodynamic roughness, the calculation formula is: rr aa == ll nno (( 22 -- dd ZZ 00 Mm )) ·&Center Dot; ll nno (( 22 -- dd ZZ 00 Hh )) KK 22 uu 22 -- -- -- (( 66 )) 其中,Z0M和Z0H分别是动量传输和能量传输粗糙度长度,d是零平面位移,z0是表面粗糙长度,u2是2m处风速;设植被高度为h,则d=0.65h,z0=0.1h,Z0M=0.1h,Z0H=0.1Z0M;2m处风速u2由CLDAS数据的10m处风速U进行换算,计算公式为:Among them, Z 0M and Z 0H are the roughness lengths of momentum transmission and energy transmission respectively, d is the zero plane displacement, z 0 is the surface roughness length, u 2 is the wind speed at 2m; if the vegetation height is h, then d=0.65h, z 0 =0.1h, Z 0M =0.1h, Z 0H =0.1Z 0M ; the wind speed u 2 at 2m is converted from the wind speed U at 10m from CLDAS data, and the calculation formula is: uu 22 == Uu [[ ll nno (( 22 -- dd zz 00 )) ]] [[ lnln (( 1010 -- dd zz 00 )) ]] -- -- -- (( 77 )) 对于MODIS无云像元,有效土壤水分的计算公式为:For MODIS cloudless pixels, the calculation formula of effective soil moisture is: Mm 00 == (( TT cc ,, maxmax -- TT sthe s ,, maxmax )) ·· Ff VV CC ++ TT sthe s ,, maxmax )) -- TT sthe s [[ (( TT cc ,, maxmax -- TT sthe s ,, maxmax )) ·&Center Dot; Ff VV CC ++ TT sthe s ,, maxmax ]] -- [[ (( TT cc ,, minmin -- TT sthe s ,, minmin )) ·&Center Dot; Ff VV CC ++ TT sthe s ,, minmin ]] -- -- -- (( 88 )) 其中,Ts是直接从MODIS的温度产品中读取的数据。where Ts is the data read directly from the MODIS temperature product. 4.根据权利要求3所述的获取全天候有效土壤水分的方法,其特征在于,所述步骤3中的估算MODIS有云像元的有效土壤水分具体为:4. the method for obtaining all-weather effective soil moisture according to claim 3, is characterized in that, the effective soil moisture of the estimated MODIS cloud pixel in the described step 3 is specifically: 计算地表阻抗:Calculate the ground impedance: rr sthe s == 11 0.0040.004 ++ 0.0120.012 ×× uu sthe s -- -- -- (( 99 )) 其中,us是地表粗糙度影响最小的高度处的风速,利用叶面积指数,叶子直径和植被高度进行估算,设植被高度为h,叶子直径为s,则us近似为:Among them, u s is the wind speed at the height where the influence of surface roughness is the smallest. It is estimated by using the leaf area index, leaf diameter and vegetation height. Assuming that the vegetation height is h and the leaf diameter is s, then u s is approximated as: uu sthe s == uu 22 ·&Center Dot; expexp -- 0.280.28 ·&Center Dot; LAILAI 22 33 ·&Center Dot; sthe s -- 11 33 ·&Center Dot; hh -- 11 33 [[ 11 -- 0.050.05 // hh ]] -- -- -- (( 1010 )) 其中,LAI是叶面积指数,从MODIS数据直接读取;Among them, LAI is the leaf area index, read directly from the MODIS data; MODIS有云像元有效土壤水分M0近似计算为:The approximate calculation of the effective soil moisture M0 of the cloudy pixel in MODIS is : Mm 00 == rr aa rr sthe s ++ rr aa -- -- -- (( 1111 )) ..
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