CN110991032B - Quantitative evaluation method for ground surface radiation balance land utilization change contribution - Google Patents

Quantitative evaluation method for ground surface radiation balance land utilization change contribution Download PDF

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CN110991032B
CN110991032B CN201911196999.0A CN201911196999A CN110991032B CN 110991032 B CN110991032 B CN 110991032B CN 201911196999 A CN201911196999 A CN 201911196999A CN 110991032 B CN110991032 B CN 110991032B
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冯徽徽
叶书朝
邹滨
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Central South University
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Abstract

The invention discloses a quantitative evaluation method for a ground surface radiation balance land utilization change contribution rate, which comprises the following steps: acquiring land utilization data and net radiation remote sensing data according to actual requirements; secondly, calculating a land use conversion track Trac according to the land use data in the step one; thirdly, calculating the unit net radiation variation average value corresponding to each type of track in each stage according to the Trac of the track in the step (II); (IV) obtaining a contribution value CON of the land use change to the net radiation change according to the calculated result in the step (III); and (V) calculating the contribution rate Z of the land use change to the net radiation according to the contribution value CON in the step (IV). Aiming at the problem that the influence of land use change on a net radiation value is difficult to distinguish by the existing empirical method and model, the method has the beneficial effect of quantitatively distinguishing the contribution of land use and other environmental elements to net radiation based on the land use track.

Description

Quantitative evaluation method for ground surface radiation balance land utilization change contribution
Technical Field
The invention relates to a quantitative evaluation method for contribution of land utilization change to earth surface radiation balance, in particular to a quantitative distinguishing method for contribution of land utilization to environmental factor change based on multi-source and multi-period remote sensing data, and belongs to the technical field of ecological environment monitoring.
Background
Solar radiation is a main energy source in the processes of ground surface heat transmission, substance transmission, exchange and the like, influences ground surface hydrothermal balance and energy circulation, and is closely related to climate change and change of ground surface ecological environment. The surface net radiation is the net solar radiation energy absorbed by the surface during the exchange of surface and solar radiation, representing the net income of surface energy, and is an important driving force for atmospheric movement. The net radiation change of the earth surface can change the sensible heat energy and the latent heat energy entering the atmosphere, so that the climate changes and the earth surface motion process is influenced. Therefore, it is important to explore the driving factors of the surface net radiation change and the influence thereof on the development of the ecological environment and human beings.
The net surface radiation includes the balance of the downward surface radiation affected by weather, temperature and other conditions and the upward surface radiation includes the solar radiation reflected by the surface and the radiation of the surface itself, which are closely related to the type of surface coverage. With the enhancement of human activities (industrialization, urbanization and the like), the intensity of land utilization change is increased, the characteristic change of the subsurface bedding surface is obvious, and the net radiation of the surface is changed. The ground utilization change and other environmental meteorological factors play an important role in revealing the environmental response characteristics of human activities in the ground surface net radiation effect.
Current methods for studying land use changes and environmental factor response characteristics are broadly divided into two categories: one is an empirical analysis method, namely according to existing land utilization data and interesting environmental factor data, establish the empirical regression model, confirm the relation between the two, this kind of method is easy to operate, easy to carry out, but can only explain the relation between the two from the statistical perspective, can't explain the effect of the change of land utilization to the environmental factor from the mechanism; the other method is a model method, namely selecting environment factors related to the radiation process to establish a model, the method can determine the effects of different elements on the environment factors by controlling the model input elements, but model errors exist in the results, and the change of the input elements has a decisive effect on the model results. Therefore, there is a need for a method that is simple and easy to implement and that can quantitatively distinguish the net radiation contribution of land use changes to the surface.
Disclosure of Invention
In view of the above-mentioned shortcomings of the prior art, the present invention aims to provide a method which is simple and easy to implement, has strong universality, and can quantitatively distinguish the contribution of land use change to the net radiation of the earth surface.
In order to solve the above problems, the present invention adopts the following technical solutions.
1. A quantitative assessment method for the contribution of surface radiation balance land utilization change is characterized by comprising the following steps:
firstly, obtaining land utilization remote sensing data and corresponding contemporaneous net radiation remote sensing data of a monitoring area;
and (II) calculating to obtain a land utilization conversion track Trac according to the land utilization remote sensing data acquired in the step (I):
(1) if the monitoring time scale is continuous years, the land use transformation trajectory Trac can be expressed as:
Figure GDA0003751074400000021
in the formula, Cl i Representing i-year land use classification data; a is the initial year, b is the end year;
(2) if the monitoring time scale is a non-continuous year, the non-continuous year is marked as: m years, n years, k years, l years, and z years, the land use transformation trajectory Trac can be expressed as:
Trac=Cl m ×10 4 +Cl n ×10 3 +Cl k ×10 2 +Cl l ×10+Cl z (2)
in the formula, Cl m ,Cl n ,Cl k ,Cl l ,Cl z Land utilization data of m years, n years, k years, l years and z years are respectively, wherein m is<n<k<l<z;
Thirdly, calculating the average value NR of unit net radiation change corresponding to each type of land utilization conversion track Trac at each time stage according to the land utilization conversion tracks Trac obtained in the second step cd
Figure GDA0003751074400000022
In the formula (II) NR cd The average value of the unit net radiation variation of the area converted from the land type c to the land type d in a fixed time period is obtained; marking the land use conversion track Trac of the area of which the land type is converted from c to d as a track T cd H is the track T cd The total number of strips; s cd And S trac,i Respectively for all tracks T cd Total area of the corresponding region and its ith track T cd The area of the corresponding region; NR (nitrogen to noise ratio) trac,i Is the ith track T cd Mean value of unit net radiance variation over the corresponding area; the right plot type c and the right plot type d both comprise: the forest land,Grasslands, agricultural lands, construction lands and water bodies;
(IV) obtaining the unit net radiation variation average value NR according to the step (III) cd Calculating to obtain: mean value of net radiation variation per unit NR corresponding to locus of variation in land type xy Average value NR of net radiation variation in unit corresponding to trace where no change occurs in land type xx
The contribution CON of land use changes to the net radiation change is:
CON=NR xy -NR xx (4)
and (V) obtaining the contribution rate Z of the land utilization to the net radiation according to the contribution value CON of the land utilization change to the net radiation change obtained in the step (IV):
Figure GDA0003751074400000031
compared with the prior art, the invention has the following beneficial effects:
the quantitative evaluation method for land surface radiation balance land use change contribution is based on generation of a land use conversion track, the net radiation change value of a land use unchanged track represents the influence of environmental meteorological factors on net radiation, the net radiation value of the land use changed track represents the comprehensive influence of land use change and the environmental meteorological factors on the net radiation, and the evaluation value of the land use change on the net radiation is obtained by eliminating the net radiation value of the land use changed track from the net radiation value of the land use changed track. Compared with the prior empirical method and model method, the method quantitatively distinguishes the effects of land utilization and meteorological factors on the net radiation of the earth surface, is easy to understand and implement, has good universality and strong generalization; in addition, the idea of the land use-based track analysis method provided by the invention provides a new idea for analyzing response characteristics of human activities to other factors.
Drawings
FIG. 1 is a schematic view of the present invention;
FIG. 2 is a diagram of classification of land utilization in the drainage area of Dongting lake;
FIG. 3 is a diagram illustrating net radiation values in the drainage area of Dongting lake;
FIG. 4 is a land use trajectory graph Trac;
FIG. 5 shows the net radiation variation values in 2001-2015 in the Dongting lake basin.
Detailed Description
The invention is described in further detail below with reference to the figures and examples.
The invention relates to a quantitative evaluation method for the contribution rate of land surface radiation balance land utilization change, which can be summarized as the following steps: acquiring land utilization data and net radiation remote sensing data according to actual requirements; secondly, calculating a land use conversion track Trac according to the land use data in the step one; thirdly, calculating a unit net radiation variation average value corresponding to each type of track in each stage by using a geospatial superposition analysis method according to the track Trac in the step (II); (IV) according to the result calculated in the step (III), the net radiation change value NR in the land use change track is used xy Subtracting the net radiation variation value NR in the unchanged track of land use xx Obtaining a contribution value CON of the land use change to the net radiation change; and (V) calculating the contribution rate Z of the land use change to the net radiation according to the contribution value CON in the step (IV).
The method aims at the problem that the influence of land use change on the net radiation value is difficult to distinguish by the existing empirical method and model, and the contribution of land use and other environmental elements to the net radiation is quantitatively distinguished on the basis of the land use conversion track.
Specifically, as shown in fig. 1, the present invention comprises the following detailed steps:
and (I) acquiring the land utilization remote sensing data and corresponding contemporaneous net radiation remote sensing data of the monitoring area according to the size of the monitoring area and the actual monitoring scale requirement. Common land use remote sensing data comprise raster type data and vector type data; if the land utilization data is of a vector type, the vector can be rasterized, and each land type is determined to have a unique grid value corresponding to the land type, for example, grid values 1-5 can be selected to respectively represent forest lands, grasslands, agricultural lands, construction lands and water bodies.
And (II) calculating a land use conversion track Trac according to the land use remote sensing data acquired in the step (I):
according to different monitored time scales, different calculation methods of the land utilization transformation track Trac are adopted:
(1) if the monitoring time scale is continuous years, the calculation formula of the land utilization conversion track Trac is as follows:
Figure GDA0003751074400000041
in the formula, Cl i Representing i-year land use classification data; a is the starting year and b is the ending year.
(2) If the monitoring timescale is a non-contiguous year, if the year is m years, n years, k years, l years, z years (m < n < k < l < z), then the trajectory is calculated as follows:
Trac=Cl m ×10 4 +Cl n ×10 3 +Cl k ×10 2 +Cl l ×10+Cl z (2)
in the formula, Cl m ,Cl n ,Cl k ,Cl l ,Cl z The land utilization data are respectively m years, n years, k years, l years and z years.
The generated land use transformation trajectory Trac provided by the invention not only reflects land use types in different periods, but also indicates the process of land use change. If the track with the track number xxyyy represents the following meaning: the land type in m and n years is x, and the land type in k, l and z years is y; the type of the usage changes from x to y during the years n to k. It should be noted that the data of the land use transformation trajectory Trac in the present invention does not have a certain dimension, and the land use transformation trajectory Trac represents a variation process.
Thirdly, calculating the average value NR of unit net radiation change corresponding to each type of land utilization conversion track Trac at each time stage according to the land utilization conversion tracks Trac obtained in the second step cd
Figure GDA0003751074400000051
In the formula (II) NR cd The average value of the unit net radiation variation of the area converted from the right-to-ground type c to the right-to-ground type d in a fixed time period is obtained; marking the land use conversion track Trac of the area of which the land type is converted from c to d as a track T cd H is the track T cd The total number of (c); s cd And S trac,i Respectively for all tracks T cd Total area of the corresponding region and its ith track T cd The area of the corresponding region; NR (nitrogen to noise ratio) trac,i Is the ith track T cd A net radiation variation value over the corresponding area; the right plot type c and the right plot type d both comprise: forest land, grassland, farm land, land for construction and water body (grid value is 1-5)
Fourthly, according to the unit net radiation variation average value of each type of track calculated in the third step, the unit net radiation variation average value on the permanent track (namely the land type unchanged area, the track numbers are xx, yy, zz and the like) represents the influence of the environmental meteorological factors such as the atmosphere, the temperature and the like on the net radiation; the average value of unit net radiation change on the change track (namely xy, xz and the like) represents the comprehensive influence of land utilization change and environmental meteorological factors on net radiation; thus, the contribution of land use changes to the net radiance is the difference between the mean of the net radiance change in units of the change trajectory and the mean of the net radiance change in units of the permanent trajectory. Taking the transformation from the land type x to the land type y contributing to the net radiation as an example, the calculation formula is as follows:
CON xy-xx =NR xy -NR xx (4)
in the formula, CON xy-xx Converting the contribution of the land type x to the net radiation of the land type y; NR (nitrogen to noise ratio) xy Is the mean value of the unit net radiance variation on the trajectory xy (i.e. the area where the right-bearing type x becomes the right-bearing type y); NR (nitrogen to noise ratio) xx The average value of the unit net radiation variation corresponding to the track with unchanged land type is obtained.
Wherein the unit net radiation variation mean value NR corresponding to the locus of the change of the land type xy Average value NR of net radiation variation in unit corresponding to trace where no change occurs in land type xx Is calculated and heldFor example, the following:
taking a stage-invariant track (track number xx) as an example, the data is calculated as follows:
Figure GDA0003751074400000052
in the formula (II) NR xx The unit net radiation variation average value of the land use type unchanged area (namely the geographical area with the track number xx) with the land types x in the period is obtained; n is the total number of xx traces; s xx And S trac,i The total area of the trace xx and the area of the ith trace thereof respectively; NR (nitrogen to noise ratio) trac,i Is the average of the unit net radiation variation over the ith trace.
Calculating the average value of net radiation variation of unit corresponding to other types of tracks in turn according to the same calculation method, such as average value NR of net radiation variation of unit corresponding to track with x-to-y type xy
Fifthly, according to the contribution value of the land use change calculated in the step (four) to the net radiation change, calculating the contribution rate of the land use change to the net radiation change, and converting the land type x into the contribution rate Z of the land type y to the net radiation xy-xx The calculation formula is as follows:
Figure GDA0003751074400000061
the following is a detailed description of a preferred embodiment of the invention:
the net radiation response of the land utilization changes of the drainage areas of the Dongtinglake regions is taken as an example.
1. MODIS land utilization data and net radiation data of 2001 and 2015 are downloaded from LAADS DAAC website and national Earth System science data center respectively according to the range and position of the Dongting lake basin.
2. Splicing and reprojection are carried out on land utilization data by using an MODIS data processing tool MRT (a projection coordinate system is consistent with net radiation data), and resolution is resampled until the net radiation data is consistent; and then clipping according to the vector boundary file of the Dongting lake basin:
(a) in order to obtain complete land utilization data of the Dongting lake basin, downloaded MODIS land utilization classification data needs to be spliced.
(b) Because the resolution and the coordinate system of the MODIS land use data are different from those of the net radiation data, the two coordinate systems and the resolution are required to be unified for calculating the net radiation values corresponding to different land use track types at the later stage, so that the MODIS land use data coordinate system is projected to be consistent with the net radiation data and the resolution is distinguished for resampling.
Note: splicing, projection and resampling of MODIS land utilization data can be completed by using an MRT tool.
(c) After the MODIS land use classification data are processed, cutting vector boundaries of the Dongting lake flow areas in ArcGIS software to obtain land use data of the Dongting lake flow areas.
3. Reclassifying the land utilization data processed in the step 2 in matlab software, and dividing the land utilization data into forest lands, grasslands, construction lands, agricultural lands and water bodies; the grid values sequentially corresponding to the forest land, the grassland, the construction land, the agricultural land and the water body are as follows: 1. 2, 3, 4, 5, as shown in fig. 2, wherein (a) represents a 2001 classification chart, i.e., Cl 2001 And (b) represents 2001 classification chart, i.e., Cl 2015
The code to reclassify the land use data in matlab is as follows:
' D: ' land utilization classification data 2001'
list_tif=dir(fullfile(path,'*.GIF'));
tif_num=length(list_tif);
[x,r]=geotiffread(fullfile(path,list_tif(1).name));
for i=1:tif_num
[a,R]=geotiffread(fullfile(path,list_tif(i).name));
info=geotiffinfo(fullfile(path,list_tif(i).name));
year=list_tif(i).name(1:4);
a(1<=a&a<=5)=1;
a(a==8)=1;
a(6<=a&a<=7)=2;
a(9<=a&a<=10)=2;
a(a==13)=3;
a(a==12|a==14)=4;
a(a==11|a==17)=5;
a(a==16)=0;
outname=['D:\CL2001.GIF'];
geotiffwrite(outname,a,R,'GeoKeyDirectoryTag',info.GeoTIFFTags.GeoKeyDirectoryTag);
end
disp('ok')
4. Annual synthesis is carried out on net radiation data in matlab, net radiation annual average value is calculated, and obtained net radiation annual average values in 2001 and 2015 are NR respectively 2001 、NR 2015 As shown in FIG. 3, wherein (a) represents the net radiation value NR in 2001 2001 And (b) represents 2015 Net radiation value, NR 2015
The code for calculating the annual mean of net radiation data in matlab is as follows:
path: 'F: \\ 2001 net radiation data';
a=dir(fullfile(path,'*.GIF'));
[x,r]=geotiffread(fullfile(path,a(1).name));
Year=a(1).name(4:7);
cla _ Year [ ' calculate ', mean ' ];
disp(cla_year);
s=zeros(size(x));
sum_dayval=zeros(size(x));
daynum=length(a);
for i=1:daynum
[ith_dayval,R]=geotiffread(fullfile(path,a(i).name));
%ith_dayval(ith_dayval==NoData)=-1
flag=ith_dayval>=0;
s=s+flag;
ith_dayval(ith_dayval<0)=0;
sum_dayval=sum_dayval+double(ith_dayval);
end
s=double(s);
mean=sum_dayval./s;
clear val flag realvaluenum add_value
outname=['F:\NR2001]
geotiffwrite (outname, mean, R); % output tif
disp ('end of run')
5. Generating a land use transformation track Trac:
Trac=Cl 2001 ×10+Cl 2015
wherein, Trac is the land utilization track, as shown in FIG. 4; cl 2001 、Cl 2015 2001, 2015 land use classification data, respectively, as shown in fig. 2. The land use change Trac locus is generated by inputting a formula b1 x 10+ b2 into a bandmath tool in ENVI software (wherein b1 and b2 respectively select 2001 and 2015 land use classification data).
19 different types of land use tracks such as 11, 12, 14, 15, 21, 22, 23, 24, 25, 33, 41, 42, 43, 44, 45, 51, 52, 54 and 55 are generated in total, and tracks with the occupation area ratio of 43 and 51 being lower than 0.01% are rejected (tracks with the occupation area ratio lower than 0.01% of the total area are considered to be caused by classification errors).
Wherein, the track number of 11 indicates that the land types in 2001 and 2015 are both forest lands (the grid values are all 1); the locus number 12 indicates that the type of the 2001-year-old land is forest land (grid value is 1), and the type of the 2015-year-old land is grassland (grid value is 2); the remaining track numbers are intended to be similar.
6. Calculating the net radiation annual average change value NR 01-15
NR 01-15 =NR 2015 -NR 2001
The calculation results are shown in fig. 5; the calculation process is realized by inputting formulas b1-b2 through a bandmath tool in ENVI software, wherein b1 and b2 respectively select net radiation data NR in 2001 and 2015 2001 、NR 2015
7. Using geospatial overlay analysis methods, according to formulae
Figure GDA0003751074400000081
Calculating the average value of the net radiation unit change corresponding to each different type of land utilization tracks Trac, wherein S cd And S trac,i Has the unit of m 2 The calculation results are as follows:
TABLE 1 mean value of net radiation change (in KW/m) between 2001 and 2015 for each trace 2 )
Figure GDA0003751074400000082
Note: according to formula in matlab software
Figure GDA0003751074400000083
The code for calculating the average value of the change of the net radiation unit corresponding to the Trac of different types of land utilization tracks is as follows:
Figure GDA0003751074400000084
Figure GDA0003751074400000091
8. calculating the contribution of the grassland to the agricultural land to the net radiation using the traces 22, 24 as examples (other land type contributions are similar to the calculation of the contribution rate);
calculating the contribution CON of the grassland converted into the agricultural land to the net radiation 24-44 Is-0.09 KW/m 2
CON 24-22 =NR 24 -NR 22 =(-1.54)-(-1.45)=-0.09(KW/m 2 )
9. Further calculating the contribution rate Z of the grassland converted into the agricultural land to the net radiation 24-44 The content was 5.84%.
Figure GDA0003751074400000092
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention has been described in detail with reference to the preferred examples, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, which should be covered by the claims of the present invention.

Claims (1)

1. A quantitative assessment method for the contribution of surface radiation balance land utilization change is characterized by comprising the following steps:
acquiring land utilization remote sensing data and corresponding contemporaneous net radiation remote sensing data of a monitored area;
and (II) calculating to obtain a land utilization conversion track Trac according to the land utilization remote sensing data acquired in the step (I):
(1) if the monitoring timescale is a continuous year, the land use transformation trajectory Trac may be expressed as:
Figure FDA0003751074390000011
in the formula of Cl i Representing i-year land use classification data; a is the initial year, b is the end year;
(2) if the monitoring time scale is a non-continuous year, the non-continuous year is marked as: m years, n years, k years, l years, and z years, the land use transformation trajectory Trac can be expressed as:
Trac=Cl m ×10 4 +Cl n ×10 3 +Cl k ×10 2 +Cl l ×10+Cl z (2)
in the formula, Cl m ,Cl n ,Cl k ,Cl l ,Cl z Land utilization data of m years, n years, k years, l years and z years respectivelyWherein m is<n<k<l<z;
Thirdly, calculating the average value NR of unit net radiation change corresponding to each type of land utilization conversion track Trac at each time stage according to the land utilization conversion tracks Trac obtained in the second step cd
Figure FDA0003751074390000012
In the formula (II) NR cd The average value of the unit net radiation variation of the area converted from the land type c to the land type d in a fixed time period is obtained; marking the land use conversion track Trac of the area of which the land type is converted from c to d as a track T cd H is the track T cd The total number of strips; s cd And S trac,i Respectively for all tracks T cd Total area of the corresponding region and its ith track T cd The area of the corresponding region; NR (nitrogen to noise ratio) trac,i Is the ith track T cd Mean value of unit net radiance variation over the corresponding area; the right plot type c and the right plot type d both comprise: woodland, grassland, agricultural land, construction land and water body;
(IV) obtaining the unit net radiation variation average value NR according to the step (III) cd Calculating to obtain: mean value of net change in unit radiation NR corresponding to locus of change in land type xy Unit net radiation variation average value NR corresponding to trace with land type unchanged xx
The contribution CON of land use changes to net radiation changes is:
CON=NR xy -NR xx (4)
and (V) obtaining the contribution rate Z of the land utilization to the net radiation according to the contribution value CON of the land utilization change to the net radiation change obtained in the step (IV):
Figure FDA0003751074390000021
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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2009057190A1 (en) * 2007-10-29 2009-05-07 Japan Agency For Marine-Earth Science And Technology Meteorological phenomena simulation device and method
CN101599142A (en) * 2009-07-07 2009-12-09 武汉大学 Land evaluation index classification quantitative method based on spatial data field
CN102567635A (en) * 2011-12-23 2012-07-11 中国水利水电科学研究院 Method for quantificationally distinguishing contributions of different factors in water cycle evolution process
CN106169014A (en) * 2016-06-15 2016-11-30 中国水利水电科学研究院 Region based on remotely-sensed data Surface sensible heat/latent heat flux inversion method and system
CN108829975A (en) * 2018-06-19 2018-11-16 中国科学院地理科学与资源研究所 The remote sensing estimation method and device of surface temperature in a few days change procedure
WO2019014120A1 (en) * 2017-07-11 2019-01-17 The Trustees Of Princeton University System and method for performing accurate hydrologic determination using disparate weather data sources

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2009057190A1 (en) * 2007-10-29 2009-05-07 Japan Agency For Marine-Earth Science And Technology Meteorological phenomena simulation device and method
CN101599142A (en) * 2009-07-07 2009-12-09 武汉大学 Land evaluation index classification quantitative method based on spatial data field
CN102567635A (en) * 2011-12-23 2012-07-11 中国水利水电科学研究院 Method for quantificationally distinguishing contributions of different factors in water cycle evolution process
CN106169014A (en) * 2016-06-15 2016-11-30 中国水利水电科学研究院 Region based on remotely-sensed data Surface sensible heat/latent heat flux inversion method and system
WO2019014120A1 (en) * 2017-07-11 2019-01-17 The Trustees Of Princeton University System and method for performing accurate hydrologic determination using disparate weather data sources
CN108829975A (en) * 2018-06-19 2018-11-16 中国科学院地理科学与资源研究所 The remote sensing estimation method and device of surface temperature in a few days change procedure

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
土地利用差异与变化对区域热环境贡献研究――以京津冀城市群为例;孙宗耀等;《生态环境学报》;20180718(第07期);第1313-1322页 *
城市地表净辐射通量的季相变化及与地表覆盖格局的关系研究;王菲菲等;《地球信息科学学报》;20180822(第08期);第1160-1168页 *

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