Mapping land cover, soil cultivation and crop establishment for nitrate sensitivity analysis using ERS InSAR data

被引:0
|
作者
Zmuda, A [1 ]
Slater, J [1 ]
Batts, A [1 ]
Seaman, E [1 ]
机构
[1] Remote Sensing Applicat Consultants Ltd, Alton GU34 5PZ, Hants, England
关键词
D O I
暂无
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
ADAS, a land and environment consultancy, is responsible for monitoring various government funded agri-environment schemes and satellite imagery is increasingly one of the data sources being used in this task. Current research has examined how ERS Tandem imagery can be used to provide information on land management and crop establishment over the autumn and winter. In winter, catchments are most at risk from nitrate leaching after soils return to full water saturation. Research has shown that ploughing in the autumn (rather than direct drilling) increases nitrate leaching and that an autumn sown crop or winter cover can decrease nitrate leaching. Thus during winter, the area and location of bare soil (particularly ploughed land) influences the degree of nitrate leaching. To successfully model nitrate movements over over catchments requires various parameters including information on the area and location of various land cover types, the presence and degree of ground cover of winter crops and the location of bare land (including evidence of whether this land has been cultivated). To river model requires nitrate various InSAR processing of 4 ERS Tandem pairs from 1995 was used to produce gee-coded multi temporal coherence and intensity images for an area of the Rivers Leam, Cherwell and Great Ouse Nitrate Vulnerable Zone in England. Thematic information derived from these images has been compared with a SPOT XS image and farmer's records collected after the ERS acquisitions. Analysis has shown that the potential for discriminating land cover and bare soil conditions is best achieved by combining multi-temporal coherence and intensity images. Data compression techniques have been used to reduce the thematic information into three channels. Pixel based classification has then been used to map autumn/winter land cover, including identifying cultivated bare soil and variation in the degree of establishment of autumn sown crops.
引用
收藏
页码:197 / 202
页数:6
相关论文
共 50 条
  • [1] Land-cover classification using multitemporal ERS-1/2 InSAR data
    Engdahl, ME
    Hyyppä, JM
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2003, 41 (07): : 1620 - 1628
  • [2] Combined land-cover classification and stem volume estimation using multitemporal ERS tandem INSAR data
    Engdahl, ME
    Pulliainen, J
    Hallikainen, M
    IGARSS 2003: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS I - VII, PROCEEDINGS: LEARNING FROM EARTH'S SHAPES AND SIZES, 2003, : 1936 - 1938
  • [3] Unsupervised land-cover classification using multitemporal ERS-1/2 Tandem INSAR data
    Engdahl, ME
    Hyyppä, J
    REMOTE SENSING FOR ENVIRONMENTAL MONITORING, GIS APPLICATIONS, AND GEOLOGY, 2002, 4545 : 45 - 52
  • [4] Integrated coastal subsidence analysis using InSAR, LiDAR, and land cover data
    Zhong, Wen
    Chu, Tianxing
    Tissot, Philippe
    Wu, Zhenming
    Chen, Jie
    Zhang, Hua
    REMOTE SENSING OF ENVIRONMENT, 2022, 282
  • [5] The integrated use of optical and InSAR data for urban land-cover mapping
    Amarsaikhan, D.
    Ganzorig, M.
    Ache, P.
    Blotevogel, H.
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2007, 28 (06) : 1161 - 1171
  • [6] MAGO SOFTWARE: USING COPERNICUS DATA FOR LAND COVER/CROP TYPE MAPPING AND CROP WATER DEMAND ESTIMATION
    Falagas, Alexandros
    Gounari, Olympia
    Karakizi, Christina
    Karantzalos, Konstantinos
    IGARSS 2024-2024 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, IGARSS 2024, 2024, : 1268 - 1272
  • [7] ERS-1 and JERS-1 SAR data analysis for soil moisture and land cover studies
    Rao, YS
    Rao, PVN
    Venkataratnam, L
    Rao, KS
    IGARSS '96 - 1996 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM: REMOTE SENSING FOR A SUSTAINABLE FUTURE, VOLS I - IV, 1996, : 163 - 165
  • [8] Landsat Analysis Ready Data for Global Land Cover and Land Cover Change Mapping
    Potapov, Peter
    Hansen, Matthew C.
    Kommareddy, Indrani
    Kommareddy, Anil
    Turubanova, Svetlana
    Pickens, Amy
    Adusei, Bernard
    Tyukavina, Alexandra
    Ying, Qing
    REMOTE SENSING, 2020, 12 (03)
  • [9] Linking Land Cover Data and Crop Yields for Mapping and Assessment of Pollination Services in Europe
    Zulian, Grazia
    Maes, Joachim
    Paracchini, Maria Luisa
    LAND, 2013, 2 (03) : 472 - 492
  • [10] Land cover mapping of Greater Mesoamerica using MODIS data
    Giri, Chandra
    Jenkins, Clinton
    CANADIAN JOURNAL OF REMOTE SENSING, 2005, 31 (04) : 274 - 282