## 2 Materials and Methods
### Data and Methodology
#### 2.2.1 Remote Sensing Data and Pre-Processing  
Landsat 7 Enhanced Thematic Mapper Plus (ETM+) Terrain Corrected (L1T), data dated 28 April 2000, was downloaded from the GloVis website ([[https://glovis.usgs.gov/](https://glovis.usgs.gov/)]([https://glovis.usgs.gov/](https://glovis.usgs.gov/)) (accessed on 15 March 2021)). This data is registered on the Worldwide Reference System-2 (WRS-2), and one tile (Path 125, Row 59) is required to cover the whole Iskandar Malaysia zone. A sentinel-2 Level-1C multispectral image dated June 28, 2019, was chosen to present the latest conditions of the study area because no Landsat image with acceptable cloud cover was available. The image was downloaded from the Copernicus Open Access Hub ([[https://scihub.copernicus.eu/](https://scihub.copernicus.eu/)]([https://scihub.copernicus.eu/](https://scihub.copernicus.eu/)) (accessed on 15 March 2021)). For both Landsat 7 and  
Figure 1: Map of Peninsula Malaysia (**a**) and the region of Iskandar Malaysia (**b**), with four rapidly developing zones (A, B, C, and D) in the region. Sentinel-2, only images with less than 20% cloud cover were used. The Semi-Automatic Classification plug-in (SCP) provided in the QGIS software [39] was used to perform the preprocessing of Landsat 7 and the Sentinel-2 images. Preprocessing, including radiometric correction and atmospheric correction based on the Dark Object Subtraction 1 (DOS 1) model and pan-sharpening model, was applied to the Landsat 7 image. The radiometric and atmospheric correction transferred the digital numbers (DN) to radiance then to reflectance. The pan-sharpening function, based on intensity computation, fused the 30 m Landsat multispectral bands (6 bands covering the visible (blue, green, red), near infrared, and shortwave infrared) with the panchromatic band to produce a 15 m spatial resolution reflectance image. The Sentinel-2 image underwent similar preprocessing steps (radiometric and atmospheric correction using DOS 1) based on the SCP. The visible bands (band 2--blue, 3--green, 4--red) and near infrared (band 8) of 10 m spatial resolution were stacked in this case. The output was a 4-band multispectral reflectance image at 10 m spatial resolution. A thresholding method based on the reflectance of the blue band (>0.25 for Landsat 7 and >0.21 for Sentinel-2) was applied to detect and mask out any cloud on the image. Note that, for both Landsat and Sentinel images, only a very low cloud cover was detected over the mangrove areas, which is the main focus of this study. Three latest MODIS products (Collection 006) at 500 m spatial resolution were downloaded, namely the MOD15A2H (Leaf Area Index, LAI) [38], the MOD17A2H (Gross Primary Production, GPP) [26], and the MCD12Q1 (Land cover type, LC) [37]. Only one tile (H28.V08) is required to cover the whole IM region. Both LAI and GPP are 8-day composite products. Full year products of 2000 and 2019 were downloaded for LAI and GPP, which consisted of 39 tiles for year 2000 (MODIS started to provide data from 18 February 2000) and 46 tiles for year 2019. Meanwhile, the yearly composite (one product per year) LC product for years 2000 and 2019 were downloaded. All the MODIS products are available from the NASA Earthdata website ([[https://earthdata.nasa.gov/](https://earthdata.nasa.gov/)]([https://earthdata.nasa.gov/](https://earthdata.nasa.gov/)) (accessed on 15 March 2021)). The MODIS Conversion Toolkit (MCTK) was used to process the MODIS products, including re-projection and quality check (QC) assessment. In order to maintain the quality  
Figure 2: The work-flow chart for image processing, classification and assessment, fragmentation, LAI and GPP analysis. of the LAI and GPP products, pixels with a QC bit-converted value below 48 were kept and extracted, referring to the MODIS product user guides [26; 38; 40]. The products were re-projected into WGS 84 projection, and the QC considered the sensor, detectors, and cloud condition issues of the product.