Geoscience Reference
In-Depth Information
detectors measure 36 spectral bands, 0.405μm~14.385μm, covering the range of the
electromagnetic spectrum. Among these bands, the 1-19 and 26 bands are for the visible and
near-infrared channels, and the remaining 16 bands are thermal infrared channels. In
addition, MODIS data have three spatial resolutions: 250 m (2 bands), 500 m (5 bands) and 1
km (29 bands). Compared with NOAA/AVHRR and MODIS data are of high spatial,
temporal and spectral resolution. Therefore, MODIS data have been widely used in a lot of
studies on land use land cover (LULC) mapping and LULC change detection at both global
and local scales (Perera and Tsuchiya, 2009; Friedl et al., 2002).
MODIS Level 1B data with 250 m resolution were used in this study. Although the number
of bands is limited, the two bands are in the red and near-infrared wavelengths, which are
among the most important spectral regions for remote sensing of vegetation. MODIS L1B
250 m radiance data have been utilized for detection of vegetative cover conversion caused
by recent significant natural events (burning and flooding) and human activities
(deforestation) (Zhan et al., 2002). MODIS L1B data with 250 m resolution in November of
2000, 2003, 2006, 2008 and 2010 were downloaded to detect changes, because the weather in
this month does not change too much and it is easier to get clear and cloudless images.
3.1.2 Other supporting data
The boundary vector data of the study area is from the National Fundamental Geographic
Information System with a scale of 1:4,000,000. It contains the information of borders
(national, province, city, county), rivers (the first, second, third class), main roads, main
railways, and residences (e.g., city and county). In this study, the border and residence data
are mainly used. In addition, local administrative maps, information from previous research
and the yearbooks of Guangxi are used as supporting data in the study.
3.2 Methods
The processing steps of the study are shown in Fig. 2. Firstly, the MODIS L1B data were pre-
processed and the study area of western Guangxi was retrieved using the border vector
data. Secondly, the images and other data were projected to the same coordinate system and
spatial resolution after geo-reference calibration. MODIS data with 250 m spatial resolution
in 2000, 2003, 2006, 2008, and 2010 were obtained with two bands of red and infrared bands,
respectively. Thereafter, two methods were used to monitor the RD: a) NDVI calculation to
identify the extent of RD; and b) analysis on land cover change after classification on the two
images. Finally, the changed information was extracted and compared. Through a statistical
analysis, the RD results were quantitatively analyzed.
3.2.1 RD identified by NDVI calculation
NDVI (Normalized Difference Vegetation Index) is a simple numerical indicator that can be
used to analyze remote sensing measurements. NDVI provides a crude estimate of
vegetation health and a means of monitoring changes in vegetation over time. Vegetation
index is extracted from the multi-spectral remote sensing data, it can quantized reflect the
plants situation and helps strengthen our interpretation of remote sensing images. As a
means of remote sensing, it is widely used in monitoring land-use cover, vegetation cover,
density assessment, crop identification and crop forecasting. It has enhanced the ability of
the classification in the topic mapping (Du, 2008).
Search WWH ::
Custom Search