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The Monitoring of Rangeland Resources Productivity of Qinghai Province Based on 3S Technologies

Author: MaXuanLong
Tutor: ChenQuanGong
School: Lanzhou University
Course: Grass industry of geographic information
Keywords: 3S grassland monitoring key pasture overgrazing
CLC: S812
Type: Master's thesis
Year: 2008
Downloads: 57
Quote: 2
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Abstract


This study calculates the grassland resource productivity of eight districts in Qinghai provinceused the route of "3S technology combined with field investigation". And based on the theory ofseasonal grazing and key pasture, after evaluation of grassland carrying capacity, furthermore,introduced the latent contribution of the product of agriculture, forestry and sidelines to wholegrazing system, and computed the degree and ratio of these contributions, at the same time,converted these factors to sheep unit. According to this study, a profoundly and systemicapprehension had been established for the utilizations of remote sensing data and relevantprocessing methods, foundation of models of yield of grass, calculations of K coefficients andentire technological flow. This study proved that, it must be admitted that the assessment methodsof grazing overload based on the theoretical stock carrying capacity have remarkable limitations,since this standard cannot reflect the real grazing utilization status on rangeland, therefore, it hasthe necessity to induce the concept of seasonal grazing and key pasture, only in this way, we canhave a more accurate judgment of the real stock carrying capacity of the grassland. Simultaneity,it must import other factors such as agriculture and forestry into the assessment of the grazingoverload, and execute some certain mathematic transformations, to make the ultimate grazingoverload ratio have the possible to reveal the true story. This study has some conclusions:1. The application of remote sensing data in grassland monitoring:In the study, the MODIS vegetation indices products that be provided for free downloading byNASA have been used for grassland productivity monitoring of Qinghai province, 2007. Thisstudy show that MODIS products have a lot of merits such as (1) more coverage; (2) moderateresolution; (3) favorable timeliness; (4) guarantee of products quality and (5) absolutely free fordownloading, thus, it has the potential ability to put in the wide-range grassland productivitymonitoring.2. The regression models of yield of grass and K coefficients:Since the significant in the nature resources and grazing utilization patterns among differentdistricts of Qinghai, it must calculate three K coefficients and regression models separatelyaccording to the dissimilar natural conditions and features of grazing. This "zoning thinking" notonly reflect the disparities of different districts, but also reflect the situation of grassland resources.The K coefficients and regression models of eight district of Qinghai province as follows:Xining: K1 = 0.882733, K2 = 0.866041, K3 = 0.673094K1 is the available grass factor, K2 is the edible forage factor, K3 is the grassland utilizationfactor, same as below.y = 0.0383x1.3173, correlation coefficient (R2) =0.4044in the formula above, y is yield of grass, x is digital number of NDVI image, same as below.Haidong: K1 = 0.857973, K2 = 0.862901, K3 = 0.680636y = 27.986x0.5306, correlation coefficient (R2) = 0.4061Haibei: K1 = 0.863196, K2 = 0.888339, K3 = 0.655066 y = 0.0156x1.3961,correlation coefficient (R2) =0.4321Huangnan: K1 = 0.907119, K2 = 0.889341, K3 = 0.654232y = 0.1384x1.2016, correlation coefficient (R2) = 0.4246Hainan: K1 = 0.883994, K2 = 0.865800, K3 = 0.674699y = 2.7992x0.7728, correlation coefficient (R2) = 0.4035Guoluo: K1 = 0.897720, K2 = 0.883677, K3 = 0.645573y = 0.0131x1.4092, correlation coefficient (R2) = 0.4091Yushu: K1 = 0.879160, K2 = 0.874059, K3 = 0.647286y = 0.2915x1.0206, correlation coefficient (R2) = 0.4710Haixi: K1 = 0.879487, K2 = 0.880886, K3 = 0.6525096y = 6.0081x0.6967, correlation coefficient (R2) = 0.40423. The contribution from products of agriculture, forestry and sidelinesBesides grazing on the grassland, there some other approaches of breeding livestock forshepherd such as supplementing feeding and sedentary etc. The contributions of these factors forentire grazing system have must be considered quantificational, only in this way; it is possible thatthe assessments of overgrazing are close to actual situation. Through certain conversion standard,the quantized contributions of these factors to grazing system are: Xining: 85.9*104SU (SheepUnit), Haidong: 103.24*104 SU, Haibei: 30.29*104 SU, Huangnan: 8.8*104 SU, Hainan: 32.7*104SU, Guoluo: 1.2*104 SU, Yushu: 4.5*104 SU, Haixi: 23.6*104 SU.4. The status of overgrazing of Qinghai province, 2007Compared with the actual amount of livestock, based on the number of key pasture carryingcapacity, and combined with contributions of products of agriculture, forestry and sidelines, theamount and ratio of grassland overgrazing of eight districts of Qinghai are as follows: Xining:69.18%, Haidong: 97.9%, Haibei: -32.2%, Huangnan: 73.3%, Hainan: 255%, Guoluo: 38.8%,Yushu: 58.4%, Haixi: -29.7%.

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CLC: > Agricultural Sciences > Livestock, animal medicine,hunting,silkworm,bee > General Animal Science > Grassland Science,prairie school
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