Land use and Cover Changes in the Northern Mountains of Pakistan; A Spatio-Temporal Change using MODIS (MCD12Q1) Time Series

Abstract

P lanning for sustainable economic, social, environmental, and land resources are critical because of population growth and global climate change (Ashraf, 2020;Matin et al., 2019). Due to the enormous burden of agriculture and urbanization, various human activities are underway to use the earth's natural re-sources, which are decreasing rapidly. Therefore, remote sensing satellite data are shown to be very useful for the analysis and mapping of land cover (Lasko et al., 2018;Levizzani et al., 2019). Even if the resulting spatial dataset has different resolutions, this change can be monitored using a GIS approach (Giuliani et al., 2020;Munsi et al., 2010). It is essential to fill in the literature about land use and land cover changes Abstract | In the sustainable management of natural resources, land use and land cover (LULC) changes play an essential role. Pakistan is rich in biodiversity and provides ecosystem services to the country's population, especially the mountains of the northern highland. These areas have experienced extensive depletion of ecosystem services and are susceptible to fast LULC changes. Real-time monitoring and assessment based on spatio-temporal are important to know such LULC changes. This study examines LULC in the northern mountains of Pakistan from MODIS (MCD12Q1) time series from 2001 to 2018. LULC was classified into ten significant classes. Findings of the data revealed that shrublands (0.33-0.17%), grasslands (45.83-41.74), and cropland (12.71-10.47) were decreased significantly. At the same time, savannas, permanent wetlands, urban and built-up lands, natural vegetation, permanent snow and ice, and barren lands increased substantially over the entire period. Due to the lack of baseline data, the LULC map will play an essential role in the sustainable management of LULC in the Hindu Kush, Karakoram and Himalayan regions of Pakistan. For the sustainable maintenance of the mountainous ecosystem, comprehensive research is recommended about these LULC vulnerabilities locally and regionally.

Changes in Carbon Dioxide Balance Associated with Land Use and Land Cover in Brazilian Legal Amazon Based on Remotely Sensed Imagery

“…In addition, Rainfall was closer to the EBF and WB classes, as they were those that had values above 2200 mm for all years of the studied period (Figure 6). With the purpose of evaluating the existence of monotonic trends in historical series of the three variables (GPP, CO 2 Flux and Rainfall) over 10 classes of land use and land cover of the BLA (EBF, DBF, MF, WSV, SV, GL, PW, CL, UBL and WB), the Mann-Kendall test was used, which is more robust in terms of deviations from normality and in non-stationarity of historical series data, compared to other parametric tests [54,56]. Trend analysis was performed by observing the Z value.…”

“…In order to quantify the temporal and spatial variations in land use and land cover in the BLA, we obtained the MCD12Q1 version 06 product from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on board the Terra and Aqua satellites [53]. This product was chosen because of its high accuracy over time and its public availability [41,[54][55][56][57]. The algorithm that processes the product (V006 Global 500 m Land Cover Type Product) is based on supervised decision tree classifications of MODIS Terra and Aqua reflectance data and provides global land cover types at yearly intervals in 500 m of spatial resolution [53].…”

“…The Type 1 classification scheme, from IGBP, was used (Table 1) between 2009 and 2019, as it is the most complete classification considering the purposes of this study [41,53,56]. To avoid mixing up atmospheric carbon estimates from land cover and use classes, we did not use the ENF, DNF, OS, BN, CS and NVM classes, since they were smaller than 1000 km 2 for all years [54]. The parameters of time and space for each type of land use and land cover were calculated using JavaScript language as input in the Google Earth Engine platform [58].…”

“…In general, the land use and land cover classifications using the MCD12Q1 product showed good accuracy for the BLA over the years studied. Studies report its high accuracy in classifying land use and land cover, mainly for relatively stable classes such as water and forests [41,[54][55][56][57].…”

Organic Amendments and Reduced Tillage Accelerate Harvestable C Biomass and Soil C Sequestration in Rice–Wheat Rotation in a Semi-Arid Environment

“…Expenditures for development and agricultural productivity have driven economic growth in Pakistan over the past two decades as land used for crops has increased from around 20 million hectares (ha) to between 23 to 24 million ha over this time [59]. However, agricultural land in Pakistan has become degraded due to the intensification of agricultural production as cropland shifts to pasture or crops/pasture become abandoned [60,61]. Agricultural expansion has also come at the expense of forests in Pakistan, as land use has shifted from natural habitat to more intensive land uses such as human occupation and agriculture.…”