Efficiency assessment of using satellite data for crop area estimation in Ukraine

被引:87
|
作者
Gallego, Francisco Javier [1 ]
Kussul, Nataliia [2 ,4 ]
Skakun, Sergh [2 ,4 ]
Kravchenko, Oleksii [2 ]
Shelestov, Andrii [2 ,3 ,4 ]
Kussul, Olga [4 ]
机构
[1] Commiss European Communities, Joint Res Ctr, Inst Environm & Sustainabil, I-21027 Ispra, VA, Italy
[2] Space Res Inst NASU SSAU, UA-03680 Kiev, Ukraine
[3] Natl Univ Life & Environm Sci Ukraine, UA-03680 Kiev, Ukraine
[4] Natl Tech Univ Ukraine, Kyiv Polytech Inst, UA-03056 Kiev, Ukraine
关键词
Remote sensing; Agriculture; Crop area; Classification; Ukraine; CLASSIFICATION METHODS; EARTH OBSERVATION; LAND-COVER; SYSTEM; CALIBRATION; REGRESSION; TM; SAR;
D O I
10.1016/j.jag.2013.12.013
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
The knowledge of the crop area is a key element for the estimation of the total crop production of a country and, therefore, the management of agricultural commodities markets. Satellite data and derived products can be effectively used for stratification purposes and a-posteriori correction of area estimates from ground observations. This paper presents the main results and conclusions of the study conducted in 2010 to explore feasibility and efficiency of crop area estimation in Ukraine assisted by optical satellite remote sensing images. The study was carried out on three oblasts in Ukraine with a total area of 78,500 km(2). The efficiency of using images acquired by several satellite sensors (MODIS, Landsat-5/TM, AWiFS, LISS-III, and RapidEye) combined with a field survey on a stratified sample of square segments for crop area estimation in Ukraine is assessed. The main criteria used for efficiency analysis are as follows: (i) relative efficiency that shows how much time the error of area estimates can be reduced with satellite images, and (ii) cost-efficiency that shows how much time the costs of ground surveys for crop area estimation can be reduced with satellite images. These criteria are applied to each satellite image type separately, i.e., no integration of images acquired by different sensors is made, to select the optimal dataset. The study found that only MODIS and Landsat-5/TM reached cost-efficiency thresholds while AWiFS, LISS-III, and RapidEye images, due to its high price, were not cost-efficient for crop area estimation in Ukraine at oblast level. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:22 / 30
页数:9
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