Trace forest conversions in Northeast China with a 1-km area percentage data model Xiangzheng Deng Qun’ou Jiang Hongbo Su Feng Wu Downloaded from SPIE Digital Library on 17 Sep 2010 to 129.174.115.95. Terms of Use: http://spiedl.org/terms Journal of Applied Remote Sensing, Vol. 4, 041893 (31 August 2010) Trace forest conversions in Northeast China with a 1-km area percentage data model Xiangzheng Deng,a,b Qun’ou Jiang,a,c Hongbo Su,a,d and Feng Wua a Chinese Academy of Sciences, Institute of Geographic Sciences and Natural Resources Research, Anwai, Beijing, 100101, China [email protected], [email protected], [email protected], [email protected] b Chinese Academy of Sciences, Center for Chinese Agricultural Policy, Beijing, 100101, China c Graduate University of Chinese Academy of Sciences, Beijing, 100049, China d Institute of Global Environment and Society, Center for Research on Environmental and Water, Maryland, 20705, USA Abstract. The purpose of this study is to examine the conversions of forests in Northeast China during 1988-2005 by using a 1-km area percentage data model (1-km APDM) with remote sensing data and to find the spatiotemporal characteristics of land conversions between forests and other land uses/covers and internal conversions between forest cover types. Data were derived from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) images of bands 3, 5, and 4 acquired in 1988, 1995, 2000, and 2005. Research results show that in the period between 1988 and 2005, the forest area in Northeast China underwent dramatic changes, and 4.11 million ha of forest area was aggregately lost because of the conversions of forests to other land uses/covers; at the same time, the forest area also gained 2.00 million ha because of the conversions from other land uses/covers to forests. The results also demonstrate the forest degradation resulting from the conversions between different forest cover types. This research demonstrates the feasibility and importance of using the 1-km APDM at a finer resolution to trace the spatiotemporal patterns of the forest conversions. Keywords: deforestation, forest area, land use, land cover, 1-km data set, Northeast China. 1 INTRODUCTION Estimates of global forest area have traditionally been obtained from country-level, ground- based surveys, in combination with cross-sectional maps and remote sensing monitoring [1]. However, there are large discrepancies in ground-based estimates of land cover information arising from differences in forest definition, processing methodology, outdated sources of information, and confusion between potential and existing vegetation [2], making it difficult to obtain spatially and temporally consistent estimations of the forest conversions at regional level. Fortunately, satellite data offer the prospect for internally consistent estimation for forest area. There are many efforts being undertaken to exploit the characters of forest area based on satellite data [3]. Compared with previous field investigation and inventory-based estimation, integrated estimation using remote sensing and inventory data can exhibit spatially explicit patterns of forest cover and the accompanying temporal changes [4]. However, to date, there are no studies estimating the forest conversions in Northeast China supported by the remote sensing data [5]. Northeast China, with a forest area of 4.99 × 105 km2 in 2005, occupies approximately 31% of China’s total forest area and maintains large areas of forest resources in the country [4,6]. In addition to being one of the most important timber production bases in China, Northeast China is the pilot region for the National Forest Protection Program, Grain for © 2010 Society of Photo-Optical Instrumentation Engineers [DOI: 10.1117/1.3491193] Received 30 Mar 2010; accepted 4 Jun 2010; published 31 Aug 2010 [CCC: 19313195/2010/$25.00] Journal of Applied Remote Sensing, Vol. 4, 041893 (2010) Page 1 Downloaded from SPIE Digital Library on 17 Sep 2010 to 129.174.115.95. Terms of Use: http://spiedl.org/terms Green project, Logging Ban Program, and others [5,7]. Therefore, studying the forest conversions and their spatial and temporal patterns in this region is of significance in managing the forests and understanding the causes and effects of deforestation in China. Because Northeast China has the largest wild forest area and the most important timber reserve in China, it is one of the national key forest zones [7]. However, both the total area and unit stocking volume of natural forest in the Northeast China Forest Zone have declined dramatically because of the forest exploitation and interventions and other human activities. Forest degradation in this zone not only has affected the long-term timber supply but also has resulted in severe ecological disasters, such as soil erosion, catastrophic flooding, and loss of biodiversity [8]. Therefore, it is necessary and imperative to detect the process, pattern, and extent of forest area changes (including the conversions with other land uses/covers as well as the internal transformation between different forest types). To detect the forest conversion accurately, we used the 1-km area percentage data model (1-km APDM) by indicating proportional forest area within each 1-km grid cell to capture information about the heterogeneity of vegetation at finer scales. By using the 1-km APDM, a grid cell containing trees with small patches of cleared areas, which would likely be categorized as "forest" in a traditional classification, could be detected and represented by an area percentage for cleared land or bare land. By doing this, the 1-km APDM can help the researchers obtain much more accurate results of land use/cover changes. In addition, the 1- km APDM is an efficient data fusion method, given that it bears all the advantages for the raster data model, which can greatly benefit monitoring and assessment for land conversion at regional or even global scales [9]. The 1-km area percentage data generated by the 1-km APDM is organized as an ArcGIS grid. The primary objective of this study is to examine the conversions of forests in Northeast China from 1988 to 2005 by using the 1-km APDM and to find the spatiotemporal characteristics of land conversions between forests and other land uses/covers and internal conversions between forest cover types. To achieve this goal, we used Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) data to develop a remote sensing– based, 1-km area percentage data set to trace the forest conversions. The motivations for developing the 1-km APDM based on the original 30-meter Landsat TM/ETM data were as follows: i) to reduce the storage size of the land use/cover database and to expedite the data analysis at 1-km scale without losing any detailed subgrid information; ii) to be comparable with the 1-km land use/cover data sets derived from Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), and other satellite sensors; and iii) to be ready to be spatially downscaled and used in most of the land surface process models, which are usually run at kilometers rather than tens of meters either because of the computation limitation or because of the coarse spatial resolution of other input variables. We hope that our research can provide information to policymakers about the conversions and some causes of forest area in Northeast China based on remote sensing data using the 1-km APDM so that forest management policy would have a more empirical basis. 2 DATA AND METHODOLOGY 2.1 Study area Northeast China (38°43′-53°34′N latitude, 115°37′-135°05′E longitude) consists of Heilongjiang Province, Jilin Province, Liaoning Province, and the eastern part of Inner Mongolia Autonomous Region and covers a total area of approximately 1.24 × 106 km2 (see Fig. 1). Journal of Applied Remote Sensing, Vol. 4, 041893 (2010) Page 2 Downloaded from SPIE Digital Library on 17 Sep 2010 to 129.174.115.95. Terms of Use: http://spiedl.org/terms Fig. 1. Location of the study area of Northeast China. 2.2 Data Remotely sensed Landsat TM/ETM data are widely used for mapping and monitoring the changes in forest area [10]. Time-series data of remotely sensed satellite imagery and ground information are used to form multi-temporal classifications of the presence or absence of forest areas. Our study uses a land cover classification data set developed by the Chinese Academy of Sciences (CAS) [11,12]. The data set is derived from Landsat TM/ETM images of bands 3, 4, and 5 with a spatial resolution of 30m × 30 m. The data set includes time series data for four periods: a) the late 1980s, including Landsat TM/ETM images for 1986-1989 (hereafter referred to as 1988 data); b) the middle 1990s, including Landsat TM/ETM images for 1995/1996 (1995 data); c) the late 1990s, including Landsat TM/ETM images for 1999/2000 (2000 data); and d) the middle 2000s, including Landsat TM/ETM images for 2004/2005 (2005 data). There are two levels of classification in the data set: level I, a classification containing 6 types of land uses/covers; and level II, a classification containing 25 types of land uses/covers [13]. More details on the classification of land uses/covers are included in the following Methodology section. 2.3 Methodology 2.3.1 Definition and interpretation Interpretation of the forest area data is an analytical process involving the investigation of photographic images, the detection and determination of forest categories, and the quantification of biometric indicators of forest stands. It also includes the determination and delimitation of the borders for both forest categories and major units of inventory and the identification of exact locations of objects.