NDLI: Afforestation parcels exact recognition based on fine remote sensing data for the conversion of cropland to forest project

Content Provider	IEEE Xplore Digital Library
Author	Xia Chaozong Zhang Yuxing Wang Weibing
Copyright Year	2012
Description	Author affiliation: Academy of Forest Inventory and Planning, State Forestry Administration, China (Xia Chaozong; Zhang Yuxing) \|\| Forest Resources Protection Office of Xinglong Forestry Bureau, Heilongjiang province, China (Wang Weibing)
Abstract	The conversion of cropland to forest project as one of the nationwide forestry key programs was started in 1999, aiming at prevention of soil erosion, water resources conservation, combating land desertification in the key areas and mitigation of global climate change. Afforestation is the primary measure of the Project. Because of low land quality, ecological species planted and short-term growing, mid-coarse satellite data is serious limited to check planting effect in many areas. With the development of remote sensing, finer images provide better choice to exactly detect the distribution of afforestation parcels and forested area of the Project. In this study, an exact automatic recognition algorithm for the Project parcels is developed. It is based on finer RS data (less than 5m spatial resolution), and integrates object-oriented, BP artificial neural network, multi-segmentation and expert knowledge, considering the differential features between trees and other land vegetation in terms of image hue, grey value, textural features, RGB and NDVI. Kangping county is taken as an example to test the algorithm at the support of 5-times SPOT5 images since 2003. The study results show that: 1) most of planted parcels can be extracted more than two years old, and the accuracy can reach 85%, 2) closed arbor planted longer than forested year limit can be clear detected, the total accuracy for forest extraction of the Project parcels exceeds 85%.
Starting Page	5971
Ending Page	5974
File Size	552960
Page Count	4
File Format	PDF
ISBN	9781467311601
ISSN	21536996
e-ISBN	9781467311595
e-ISBN	9781467311588
DOI	10.1109/IGARSS.2012.6352248
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-22
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Forestry Vegetation Remote sensing Feature extraction Accuracy Satellites Monitoring exact extraction Conversion of cropland to forest project fine RS data object-oriented
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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