CN108051565B - The quick monitoring method of large scale desertification - Google Patents
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Abstract
The invention discloses a kind of quick monitoring methods of large scale desertification, it is intended to excavate it is towards large scale, based on easy obtain data, more quick, accurately desertification monitoring method.Method includes the following steps: choosing research time domain, period is divided；Research area is chosen, and obtains cities and towns, waters, forest, the variation in six periods of farmland using LUCC data；It is to close on the average value of 3 years NDVI data for each period NDVI data definition；Using Decision-Tree Method, Grassland information and primary desert information are obtained using NDVI；Non- Desertification and primary desert area are deducted using research area, to obtain Desertification；15 degree of the gradient of correction is carried out using auxiliary dem data.Method of the invention is avoided the huge workload of human interpretation, is provided scientific basis for desertification land control using the data for being easier to obtain, to instruct Desertification Control, desertification decision with important practice significance.
Description
Technical field
The present invention relates to ecological protection technical fields, and in particular to a kind of fast slowdown monitoring side of large scale desertification
Method.
Background technique
The some areas such as China Inner Mongol, Xinjiang deeply is perplexed by desertification, influence of the desertification to China mainly include with
Under several aspects: first is that endanger agricultural development, desertification is mainly reflected in soil sandyization to the harm of agricultural, and seedlings of cereal crops arid causes
It is buried extremely or by dust storm, while farmers' income is unable to get guarantee；Second is that endangering grassland, deterioration of grasslands caused by desertification makes
Advantage grass seeds suitable for livestock edible gradually decreases, or even completely loses, and grassland capacity for raising livestock on the grasslands greatly declines；Third is that endangering water money
Source, desertification causes river, reservoir, water channel blocking, 1,600,000,000 tons of the average annual sediment transport in the Yellow River, wherein just there is 1,200,000,000 tons to come from desertification
Area；Fourth is that blocking traffic, desertification causes railway bed, bridge, culvert damage in some areas, makes highway subgrade, road surface
Sand forces highway communication to be interrupted, and influences the normal takeoff and landing of aircraft；Fifth is that human health is threatened, according to monitoring, China city
City's air pollutants are mainly finely ground particles, this is closely related with desertification, dust pollution the production of the wide geographic area people
Living environment affects people's health；Sixth is that leading to poverty, according to investigations, the 1/4 of national people in the countryside is with living in desertification
Area, agriculture value is only the 34.2% of average national level per capita, is the 1/5 of eastern region.According to statistics, China every year because
Economic loss caused by desertification is up to 54,000,000,000 yuan, and desertification aggravates regional poverty degree.
Therefore, monitoring desertification dynamic, especially in the fast slowdown monitoring desertification dynamic change characterization of country scale, and herein
On the basis of study driving factors and predict its future developing trend, for desertification land control, improve husky area's ecological environment with
Peasants and herdsmen's sustainable livelihoods have great importance and realistic price.
In recent years, China pays much attention to the improvement to Desertification, implements a series of measures, desertification total area
It is controlled, the pattern and severity of desertification are also varied widely in ground section.For this reality for grasping desertification
Dynamic change is applied, scholars attempt to be monitored the certain areas of China's desertification in different times, the method utilized
Mostly be using " 3S technology ", using remote sensing image as data acquisition information source: such as Wang Tao utilizes sand in 1977,1,986 two
Desertization data and remote sensing image in 2000,2,005 two are data source, husky in the past 30 years to Mu Us Shadi and surrounding area
(Guo Jian etc., 2008) is analyzed and studied to desertization dynamic changing process；Fan Yahui etc. utilizes RS and GIS technology, with TM, ETM+
It influences to be information source, Remote Sensing Dynamic Monitoring (Fan Yahui etc., 2011) is carried out to Aibi Lake Area desertification in the past 30 years；Section
Heros etc. are based on remote sensing technology, using Landsat TM/ETM image as data source, using the method for visual interpretation, to autonomy for Tibet
Area's desertification is monitored and analysis and research (section hero etc., 2014).
Above-mentioned desertification dynamic monitoring method is taken a broad view of, is focused mostly in terms of regional scale, although result is more accurate,
If being applied in the monitoring process of large scale and often wanting a large amount of image of visual interpretation, the process of follow-up data processing is also more multiple
It is miscellaneous, it is time- and labor-consuming.
Therefore, towards large scale, based on easy obtain data, more quick, accurately desertification monitoring method urgent need
It is studied to find and carry out practical application.
Summary of the invention
The technical problem to be solved in the present invention is to provide a kind of quick monitoring methods of large scale desertification, to reach
Desertification change in time and space information can be grasped in time, and then effectively implements macro-management, provide section for desertification land control
Learn according to purpose.
In order to solve the above technical problems, the technical thought that the present invention uses is as follows:
Using the data for being easier to obtain, is handled by simple SPSS, ArcGIS, avoid the huge workload of human interpretation
For the purpose of, quick desertification monitoring method is explored.
Not overnight, the monitoring of long-term sequence can obtain desertification dynamic evolution process to Desertification Process, examine
The accessibility of data is considered, for example, choosing 1981-2010 as research time domain, simultaneously because close period desertification is invaded
Erosion process is not obvious, therefore search time is divided into 1980,1990,1995,2000,2005,2,010 6 periods.Basis
Geodata, land use/cover (LUCC) data, NDVI data are the data for being easier to obtain, therefore it is administrative to choose the whole nation
Zoning map studies area to obtain, and obtains cities and towns, waters, forest, the variation in six periods of farmland using LUCC data；For each
Period NDVI data definition be close on the average value of 3 years NDVI data, such as LUCC data used in 1980 periods be 1981,
1982, the average value of three annual data of nineteen eighty-three；Since the mostly animal husbandry of research area is flourishing, grassland is more, grassland area it is larger and
It easily degenerates, can not preferably obtain its real-time change trend using LUCC information, and NDVI can preferably reflect coupling relationship
To obtain the Spatial-Temporal Change Trend of non-Desertification, therefore this research uses Decision-Tree Method, is obtained using NDVI
Grassland information and primary desert information deduct non-Desertification and primary desert area using research area, to obtain sand
Desertization area.
Detailed technology scheme of the present invention is as follows:
Design a kind of quick monitoring method of large scale desertification, comprising the following steps:
(1) research time domain is chosen, period is divided；
(2) research area is chosen, and obtains cities and towns, waters, forest, the variation in six periods of farmland using LUCC data；
(3) Decision-Tree Method is used, obtains Grassland information and primary desert information using NDVI；For each period
NDVI data definition is to close on the average value of 3 years NDVI data；
(4) non-Desertification and primary desert area are deducted using research area, to obtain Desertification.
It is found through on-the-spot investigation, monitoring section gradient larger area vegetative coverage is all right, therefore can further use
Dem data is assisted to carry out 15 degree of the gradient of correction, i.e., the deductible abrupt slope region for being greater than 15 degree.
Further, the Grassland information and/or when primary desert information extraction threshold value determination the following steps are included:
(1) turn line function using face in ArcGIS crossover tool and desertification monitoring geographical unit polar plot is converted into geography
Unit linear file；
(2) a certain number of (such as 100) meadows and/or original are chosen in each geographical unit using GoogleEarth
Raw desert sampling point；
(3) figure layer text will be converted to containing the sampling point information kml file that upper step is chosen by crossover tool in GIS
Part；
(4) the average annual NDVI mean value of corresponding points is extracted with raster symbol-base device；
(5) dbf file and the preservation of corresponding sampling point NDVI mean value are opened by Excel；
(6) the Excel table saved, line frequency of going forward side by side analysis are opened with SPSS；
(7) meadow and/or primary desert biology NDVI value frequency distribution table are obtained, in conjunction with actual conditions by meadow and/or
The threshold value in primary desert is set to the NDVI value at frequency 80%；
(8) it counts the threshold value on each geographical unit meadow and/or primary desert and generates meadow and/or primary desert threshold value
Table.
Further, the meadow and/or primary desert extract the following steps are included:
(1) data source is that Desertification in Northern China monitors geographical unit grid map, utilizes spatial analysis tool reclassification function
Can, target geographic unit is assigned a value of 1, remaining is assigned a value of 0；
(2) different times NDVI grid map is operated gained grid map with step (1) in raster symbol-base device to be multiplied, is obtained
One geographical unit NDVI information；
(3) reclassification function is utilized, reclassification, meadow and/or primary sand are carried out according to meadow and/or primary desert threshold value
Desert is assigned a value of 1, and other assignment 0 obtain target geographic unit Grassland information；
(4) 20 geographical unit meadows and/or primary desert information are spliced, obtains research area meadow and/or primary sand
Unconcerned data.
Preferably, the Desertification is divided into slight desertification, moderate desertification, severe desertification, pole severe desert
Change four grades.
Further, the grade scale of the Desertification are as follows: according to the meadow threshold value table of acquisition and primary desert threshold
After being worth table information analysis, NDVI value at the 25% of two-value difference is set to pole severe Desertification and severe Desertification
Critical value；NDVI value is set to the critical value of moderate Desertification Yu severe Desertification at 50%；NDVI value is set at 75%
The critical value of slight Desertification and moderate Desertification.
Preferably, all grids, vector data unify resampling or are converted to the spatial data that resolution ratio is 8km × 8km.
Compared with prior art, the beneficial technical effect of the present invention lies in:
1. method of the invention is handled using the data for being easier to obtain by simple SPSS, ArcGIS, avoid artificial
The huge workload of interpretation, explores quick desertification monitoring method.
2. the present invention provides a kind of quick, simple, accurate large scale desertification monitoring methods, and pass through representative region
Application, precisely explore the dynamic change that Desertification Area in Northern China towards large scale is desertified.
Space-variant when 3. the quick monitoring method of large scale desertification provided by the invention can grasp desertification in time
Change information, and then effectively implement macro-management, provide scientific basis for desertification land control, to instruct Desertification Control,
Desertification decision has important practice significance.
Detailed description of the invention
Fig. 1 is Desertification Area in Northern China land use/cover figure in 2010；
Fig. 2 is Technology Roadmap；
Fig. 3 is desertification monitoring flow chart；
Fig. 4 is that meadow threshold value determines flow chart；
Fig. 5 is 1980-2010 north of China land-use map.
Specific embodiment
Illustrate a specific embodiment of the invention with reference to the accompanying drawings and examples, but following embodiment is used only in detail
It describes the bright present invention in detail, does not limit the scope of the invention in any way.
Operation involved in the examples below is routine operation unless otherwise instructed；Related calculation method
Or data processing method is unless otherwise instructed conventional method.
Embodiment one: example area prepares
As shown in Figure 1, Desertification Area in Northern China is mainly concerned with Inner Mongol, Xinjiang, Qinghai, Gansu, Sichuan, peaceful
The north such as summer, Shanxi, Shaanxi extreme drought, arid, semiarid, Semi-humid area 222 Qi county.
Desertification is distributed area substantially between 77 ° of 14 ' E-122 ° 41 ' E, 32 ° of 43 ' N-49 ° 35 ' N, far from ocean, depth
Inland is occupied, ocean air-flow is not easy to reach, and forms apparent temperate zone, cool temperature zone continental climate, while these area mostly precipitation
Amount is few, and precipitation is concentrated, and dry, illumination is strong, more strong wind weathers, and the harsh weather disaster such as sandstorm, heavy rain, arid occurs
Frequently.
According to monitoring section geographical location and climatic characteristic be divided into Northwest arid district, Three River Sources areas, the Inner Mongol and
The area Along The Great Wall San great Sha.To guarantee monitoring result accuracy, the area San great Sha is further divided into 20 desertification emphasis prisons
Geographical unit is surveyed, is shown in Table 1.
1 desertification monitoring key area full edition of table
。
Embodiment two: data preparation
It monitors data source used and is shown in Table 2.
In view of resolution ratio minimum in all data, all grids, vector data are unified resampling or turned by the present invention
It is changed to the spatial data that resolution ratio is 8km × 8km.
2 basic data source of table
。
Embodiment three: technology path
Utilize multi-source data, including geo-spatial data, multi-temporal remote sensing data, altitude data, land use data etc.
North of China desertification is monitored, shown in particular technique route map 2.Desertification monitoring overall flow is as shown in Figure 3.
Example IV: result is shown
(1) non-Desertification identification
Non- desertification identification process mainly includes that meadow threshold value determines, meadow is extracted, and cities and towns, waters, forest, farmland are extracted
Three processes.
1. meadow threshold value determines
Present invention research is dedicated to avoiding the visual interpretation of larger workload, fast slowdown monitoring desertification dynamic process, for
The extraction on meadow is reached using GoogleEarth with GIS, SPSS simple process.
Process is as shown in Figure 4.
Specific step is as follows:
(1) desertification monitoring geographical unit polar plot is converted firstly, turning line function using face in ArcGIS crossover tool
For geographical unit linear file；
(2) 100 meadow sampling points are chosen in each geographical unit using GoogleEarth；
(3) figure layer file is converted to containing 100 sampling point information kml files for what is obtained by crossover tool in GIS；
(4) the average annual NDVI mean value of corresponding points is extracted with raster symbol-base device；
(5) dbf file and the preservation of corresponding sampling point NDVI mean value are opened by Excel；
(6) the Excel table saved, line frequency of going forward side by side analysis are opened with SPSS；
(7) meadow NDVI value frequency distribution table is obtained, the NDVI being set to meadow threshold value in conjunction with actual conditions at frequency 80%
Value；
(8) it counts each geographical unit meadow threshold value and generates meadow threshold value table.
2. meadow is extracted
Meadow, which is extracted, mainly completes by ArcGIS, and operating process is as follows:
(1) data source is that Desertification in Northern China monitors geographical unit grid map, utilizes spatial analysis tool reclassification function
Can, target geographic unit is assigned a value of 1, remaining is assigned a value of 0；
(2) different times NDVI grid map is operated gained grid map with (1) in raster symbol-base device to be multiplied, obtains one
Geographical unit NDVI information；
(3) reclassification function is utilized, reclassification is carried out according to meadow threshold value, meadow is assigned a value of 1, other assignment 0, obtains mesh
Mark geographical unit Grassland information；
(4) 20 geographical unit Grassland informations are spliced, obtains research area meadow data.
3. cities and towns, waters, forest, farmland are extracted
Mask process is carried out with research area and obtains research area's land use data, according to land use data to cities and towns, water
Domain, forest, agricultural land information extract, using reclassification function by second level land use pattern reclassification be level-one land use
Type.
Grassland information and cities and towns, waters, forest, agricultural land information are summarized, in addition, carrying out school using grade information
Just, the gradient is extracted first and be greater than 15 degree of information, then carry out research area's mask process, obtain research area and be greater than 15 degree of gradient areas
Information.Inevitably it will appear during the extraction process part is gloomy at figure since meadow is obtained according to NDVI using raster symbol-base device
The phenomenon that other informations such as woods or farmland are identified as meadow, therefore will appear land use pattern particular weight in generation figure
It closes, control Google earth discovery intersection is that meadow is more, therefore uniformly divides meadow into.According to dividing for above-mentioned use again
Class mode continues reclassification and obtains non-desertification data.
(2) primary desert identification
Primary desert identification uses mode identical with meadow.
(3) Desertification obtains
Desertification identification deducts non-Desertification using research area, then deducts the mode in primary desert.It is same
It is handled in ArcGIS, mode of operation are as follows: merge obtained non-desertification data with primary desert data, due to non-sand
Desertization area, primary desert area are all the data finally to be obtained, therefore in reclassification are divided into the two different classes of, are remained
Leeway area, that is, Desertification is divided into one kind.
(4) desertification is classified
Desertification, which is not showed only as non-Desertification, becomes Desertification, while also including the variation of Desertification Degree
Process, it is therefore necessary to by desertification grade determination.This research by Desertification be divided into slight desertification, moderate desertification,
Four severe desertification, pole severe desertification grades.Stage division is the meadow threshold value table and primary desert threshold value according to acquisition
NDVI value at the 25% of two-value difference is set to facing for pole severe Desertification and severe Desertification after analysis by table information
Dividing value；NDVI value is set to the critical value of moderate Desertification Yu severe Desertification at 50%；NDVI value is set to gently at 75%
Spend the critical value of Desertification and moderate Desertification；Four kinds of degree are obtained using reclassification function in spatial analysis tool
Desertification.
It obtains including non-Desertification, slight Desertification, moderate Desertification, severe sand using splicing function
Desertization area, pole severe Desertification, six kinds of the primary desert area Desertification in Northern China grid maps classified.
3 meadow of table and desertification threshold value table at different levels
。
Five, example area result is shown
Above-mentioned steps obtain 1980,1990,1995,2000,2005,2,010 6 phase Desertification in Northern China grid maps as schemed
Shown in 5.
The present invention is described in detail above in conjunction with drawings and examples, still, those of skill in the art
Member is it is understood that without departing from the purpose of the present invention, can also carry out each design parameter in above-described embodiment
Change, forms multiple specific embodiments, is common variation range of the invention, is no longer described in detail one by one herein.
Claims (6)
1. a kind of quick monitoring method of large scale desertification, which comprises the following steps:
(1) research time domain is chosen, period is divided；
(2) research area is chosen, and obtains cities and towns, waters, forest, the variation in six periods of farmland using LUCC data；
(3) Decision-Tree Method is used, obtains Grassland information and primary desert information using NDVI；For each period NDVI number
According to being defined as closing on the average value of 3 years NDVI data；
When the Grassland information and primary desert information extraction threshold value determination the following steps are included:
A. turn line function using face in ArcGIS crossover tool and desertification monitoring geographical unit polar plot is converted into geographical unit
Linear file；
B. a certain number of meadows and primary desert sampling point are chosen in each geographical unit using GoogleEarth；
C. the obtained information kml file containing the quantity sampling point is converted to by figure layer file by crossover tool in GIS；
D. the average annual NDVI mean value of corresponding points is extracted with raster symbol-base device；
E. dbf file and the preservation of corresponding sampling point NDVI mean value are opened by Excel；
F. the Excel table saved, line frequency of going forward side by side analysis are opened with SPSS；
G. meadow and/or primary desert biology NDVI value frequency distribution table are obtained, in conjunction with actual conditions by meadow and primary desert
Threshold value be set to the NDVI value at frequency 80%；
H. it counts the threshold value on each geographical unit meadow and primary desert and generates meadow and primary desert threshold value table；
(4) non-Desertification and primary desert area are deducted using research area, to obtain Desertification.
2. the quick monitoring method of large scale desertification according to claim 1, which is characterized in that in the step
(4) in, using auxiliary dem data acquired results are carried out with 15 degree of the gradient of correction.
3. the quick monitoring method of large scale desertification according to claim 1, which is characterized in that the step
(3) in, the meadow and/or primary desert extract the following steps are included:
A. data source is that Desertification in Northern China monitors geographical unit grid map, will using spatial analysis tool reclassification function
Target geographic unit is assigned a value of 1, remaining is assigned a value of 0；
B. different times NDVI grid map is operated gained grid map with step (1) in raster symbol-base device to be multiplied, obtains one
Geographical unit NDVI information；
C. reclassification function is utilized, reclassification is carried out according to meadow and/or primary desert threshold value, meadow and/or primary desert are assigned
Value is 1, other assignment 0 obtain target geographic unit Grassland information；
D. 20 geographical unit meadows and/or primary desert information are spliced, obtains research area meadow and/or primary desert number
According to.
4. the quick monitoring method of large scale desertification according to claim 1, which is characterized in that in the step
(4) in, the Desertification is divided into slight desertification, moderate desertification, severe desertification, pole severe desertification four etc.
Grade.
5. the quick monitoring method of large scale desertification according to claim 4, which is characterized in that the desertification
The grade scale in area are as follows: after the meadow threshold value table of acquisition and primary desert threshold value table information analysis, by two-value difference
NDVI value is set to the critical value of pole severe Desertification and severe Desertification at 25%；NDVI value is set to moderate sand at 50%
The critical value in desertization area and severe Desertification；NDVI value is set to slight Desertification with moderate desertification at 75%
The critical value in area.
6. the quick monitoring method of large scale desertification according to claim 1, which is characterized in that all grids,
Vector data unifies resampling or is converted to the spatial data that resolution ratio is 8km × 8km.
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| CN114202551B (en) * | 2021-12-10 | 2022-06-03 | 中国科学院地理科学与资源研究所 | Grading drawing method and grading drawing device for karst stony desertification |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1924611A (en) * | 2005-08-29 | 2007-03-07 | 王长耀 | Land deterioration (desert) evaluation parameter remote control inversion and supervision technique method |
| CN102915616B (en) * | 2012-05-11 | 2015-07-01 | 新疆大学 | Grid-accumulation-type regional land desertification early-warning method |
| CN106548017A (en) * | 2016-10-25 | 2017-03-29 | 中国科学院地理科学与资源研究所 | A kind of ecological construction data processing method based on LU data and NDVI data |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1924611A (en) * | 2005-08-29 | 2007-03-07 | 王长耀 | Land deterioration (desert) evaluation parameter remote control inversion and supervision technique method |
| CN102915616B (en) * | 2012-05-11 | 2015-07-01 | 新疆大学 | Grid-accumulation-type regional land desertification early-warning method |
| CN106548017A (en) * | 2016-10-25 | 2017-03-29 | 中国科学院地理科学与资源研究所 | A kind of ecological construction data processing method based on LU data and NDVI data |
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