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Mapping Forest Cover in Northeast China from Chinese HJ-1 Satellite Data Using an Object-Based Algorithm.

Chunying Ren1, Bai Zhang2, Zongming Wang3

  • 1Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China. renchy@iga.ac.cn.

Sensors (Basel, Switzerland)
|December 19, 2018
PubMed
Summary

Accurate forest mapping in Northeast China was achieved using HJ-1 imagery and object-based analysis. This new map provides reliable data for carbon budget and ecological models, improving upon existing global datasets.

Keywords:
GlobCoverHJ-1 imageryMCD12Q1Northeast Chinaforest mappingobject-oriented classification

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Area of Science:

  • Remote Sensing and Geospatial Analysis
  • Forest Ecology and Carbon Cycle Research
  • Environmental Monitoring

Background:

  • Forests are critical components of the global carbon budget and ecological processes.
  • Accurate forest cover mapping is essential for reducing uncertainties in terrestrial carbon balance estimations.
  • A rapid and reliable regional forest mapping method is needed.

Purpose of the Study:

  • To map forest and subcategories in Northeast China using high spatio-temporal resolution HJ-1 imagery.
  • To develop an operational method for rapid regional forest mapping.
  • To assess the accuracy and utility of the derived forest map compared to global datasets.

Main Methods:

  • Object-based image analysis (OBIA) combined with decision tree classification.
  • Utilized multi-temporal HJ-1 satellite imagery and time series vegetation indices to capture phenology.
  • Validated the forest map using ground truth data from field surveys.

Main Results:

  • Achieved a high overall accuracy of 0.91 ± 0.01 for the forest map.
  • The HJ-1-based forest area was larger than that from GlobCover 2009 and MCD12Q1 2009, closely matching national statistics.
  • Identified spatial disagreements primarily in specific plain and mountain regions.

Conclusions:

  • High-resolution HJ-1 imagery and OBIA provide a reliable method for regional forest mapping.
  • Existing global land cover products may contain uncertainties in forest subcategory information.
  • The derived HJ-1 forest products are valuable inputs for biogeochemical and carbon cycle models.