INTRODUCTION
Background of the Study
LULC changes (LULCC) provide a clear and wide range of perspectives that include human population, climate change, environmental conservation, land use planning, resource management and sustainable development (Alam et al., 2019; . Kumar et al., 2015; Parsa & Salehi, 2016 ). LULC studies justify LULCC to quantitatively improve the understanding of global environmental change and sustainability (Manandhar et al., 2010 as cited in Mawenda et al., 2020). These studies attempt to explain the occurrence of change, types of land cover undergoing change and transformation, rates at which such changes occur, and the factors that contribute to these changes (Loveland & Acevedo, 2006 as cited in Alam et al., 2019).
Objectives of the Study
Scope and Limitations of the Study
It is in the sense that the tools provide quantitative measurements of landscape components providing essential knowledge for decision makers in addition to qualitative assessments (Appiah et al., 2015). While in mountainous (rural) areas, Tadese et al. 2020) observed the expansion of agricultural land and built-up area at the expense of forest and scrub in the Awash River Basin. Ultimately, citing the interdependence of environmental components, such changes affect human well-being due to the reduced availability of ecosystem services in communities (Karki et al., 2018).
This study involved remote sensing approach, which uses multi-date satellite imagery to quantify LULCC in the study area. They also have QA bands and intermediate bands used in the calculation of surface temperature (ST) products (Google, n.d.). They also have QA bands and intermediate bands that are used in the calculation of the ST products (Google, n.d.).
The LULC classification scheme of the local government unit was used to identify the land cover types. Landscape statistics were obtained after processing the LULC maps for the three temporal points using the LecoS plugin of the QGIS application, which provided crucial information in quantifying LULCC in the landscape of Cadiz City, Negros Occidental. In the first ten-year period, LULC changes in the landscape of Cadiz City, Negros Occidental have revealed some remarkable information, shown in Table 4.2 and Figure 4.7.
In fact, this class dominates the landscape changes in the study area, although development is limited to the city center. Furthermore, the SRA-DA's Sugar Statistics report (Appendix B) shows declining sugarcane acreage over the past five consecutive years (SRA, n.d.). Overall findings show that built-up areas indeed dominated the LULC changes in the landscape of the study area.
This is mainly due to rising sea water levels confined to the lower parts of the cityscape, which have been converted into commercial aquaculture areas. Land use and forest cover dynamics. in northeast Addis Ababa, central highlands of Ethiopia.
REVIEW OF RELATED LITERATURE
METHODOLOGY
Description of the Study Area
Cadiz is a coastal city and a northern gateway to economic services in the province of Negros Occidental. The city faces the Visayan Sea to the north, Manapla Municipality and Sagay City to the west and east, as shown in Figure 3.1 respectively, while part of the NNNP occupies the southern border. Furthermore, the calculated population density is 302 inhabitants per square kilometer or 783 inhabitants per square mile.
The approximate coordinates where the city center lies are 10° 57' N, 123° 18' E, in the northern part of the island of Negros and the estimated elevation is 5.4 meters or 17.6 feet above mean sea level (AMSL) ( Cadiz, Province of Negros Occidental, n.d.).
Acquisition of Datasets
Two satellites (Landsat 7 and 8-9) captured images of the study area at selected temporal points above. The dataset contains four visible and near infrared (VNIR) bands and two shortwave infrared (SWIR) bands processed to orthorectified surface reflectance, and one thermal infrared (TIR) band processed to orthorectified surface temperature. The dataset contains five VNIR bands and two SWIR bands processed to orthorectified surface reflectance, and one TIR band processed to orthorectified surface temperature.
The bands obtained from Collection 2 Level 1 (C2 L1) Tier 1 of the USGS database were used for all temporal points (http://earthexplorer.usgs.gov/). Preprocessed USGS images provided systematic, radiometric, geometric, topographic data with terrain precision data of the highest quality level 1 (L1TP), suitable for time series analysis (USGS, 2016). While the shapefile containing the political boundary information of Cadiz City was extracted from the PhilGIS website (http://philgis.org/).
Furthermore, Cadiz City lies between two areas captured in the World Reference System (WRS), a Landsat data annotation system that allows easy access, as well as cataloging and reference of images transmitted by different satellite sensors .
Image pre-processing and classifications
The development of a training set in classifying and interpreting the image was based on local knowledge and field observations of the study area (Tadese et al., 2020). It used an algorithm that can quantitatively calculate the variance and covariance of the spectral response patterns and assign each pixel to the class it is highly associated with (Shalaby & Tateishi, 2007). The LULC classification scheme in Table 2 includes built-up, water, canopy and short vegetation, while a cloud class is added simply to account for the presence of clouds covering one of the previous classes given its impossible exclusion from the images.
When dealing with cloud cover, cloud layers from three images were combined to achieve comparable cloud cover for images in the three time points and were further subjected to cloud masking to later exclude their class when rasterizing landscape statistics with the LecoS plugin. Areas covered with trees and other tall vegetation. Sugar cane fields (agriculture), grasslands and some barren areas. However, no other methods were used to process these LULC classes (and the LULC maps) apart from the ones mentioned above, which were also expected to introduce some processing errors, but no ground validation was performed considering the pandemic, when this was difficult because movements were limited.
LULC Change Detection Analysis
However, this analysis does not take into account the areas covered by clouds, although it can be classified into any of the previous classes depending on the location on the LULC map presented in Figures 4.4, 4.5 (page 25) and 4.6 ( page 26). The increase in this class can be attributed to the rising sea level, where more water is limited in the lowlands, which are converted into commercial ponds for the aquaculture industry. Data shows that the LULCC rate has almost doubled in the second period compared to the first, while the overall LULCC rate appears at 114.43% in 20 years (Table 4.4).
As for the short vegetation, it is first seen to increase as a result of the expansion of sugar cane fields as a way of increasing sugar production in the mill district. This in turn affected urban migration patterns in the area as this opened up new opportunities for the population. This presented important policy considerations for the local government in dealing with disaster risk reduction and climate adaptation strategy as cited in Ishtiaque et al.
A large population lives in open coastal areas where strong wind, storms and large waves destroy their homes exposing people to potential environmental hazards. This study provided the assessment of LULC changes in the landscape of the city of Cadiz, Negros Occidental from 2001 to 2021 by analyzing LULC classes and determining and comparing the degree of LULCC in the analysis of two 10-year periods and an overall analysis in 20 years. using geospatial techniques. Moreover, the tent class is concentrated in the mountainous part while the built-up and water areas in the lowlands.
Water areas have been observed to follow an increasing trend in the last 20 years, as more seawater is confined in the lower part of the urban landscape, which in turn has been converted into commercial aquaculture sites. In addition, the degrees of LULCC are also expected to vary, but still in the same direction as claimed in the findings. It is recommended that future studies in the landscape of Cadiz City, Negros Occidental should be conducted using less to no, if possible, cloud cover so that generalizations can be made for the entire study area to arrive at proper and more conclusive findings to connect better. LULCC versus environmental management as a prerequisite for pro-active decision-making.
Other recommendations include the use of various technological methods such as the Boolean Operation in the study of LULCC in the study area to quantify them. Rapid urban growth in Kathmandu Valley, Nepal: Monitoring land cover land use dynamics of a Himalayan city with Landsat imagery.
RESULTS AND DISCUSSION
Analysis of 2001, 2011, & 2021 LULC classes
First period LULC Change Detection Analysis
The increase of this class is the result of the expansion of agricultural land (sugarcane fields) as it is pushed higher in the highland areas that reach the lower points of the Northern Negros Natural Park (NNNP). These outward expansions have led to the establishment of 132.5 MW solar power project in Cadiz City which is considered as Southeast A ia la geola fa m in 170 ha of land (Embassy of France in Manila, n.d.; Vena Energy, 2019), the foundation of 8,742 housing units- Yolanda resettlement projects across 10 sites in the study area (Samillano, 2017) and the construction of shopping malls, and subdivisions taking place along main and secondary road networks. Moreover, urban growth is manifested in the construction of new concrete buildings (impervious surfaces) at the expense of green spaces leading to a shift in urban microclimate characterized by higher temperatures in which temperature gradient is observed when one enters the city center.
However, coverage is observed to have increased especially during the second period, which is a positive indicator of the successful implementation of various environmental programs aimed at reversing forest and biodiversity losses. Assessment of land use and land cover change and its drivers in Battambang Province, Cambodia from 1998 to 2018.
