Assessment of above-ground biomass and carbon loss from a tropical dry forest in Mexico

Primary forests in seasonally dry tropical regions have undergone intense land-use/cover change, ranging from widespread shifting agriculture to land clearing for livestock production systems, and selective logging. Despite the importance of tropical dry forests (TDF), little is known about the implications of carbon (C) emissions from deforestation in local, national, and global scales. Therefore, the main objective of this study is to quantify and understand the processes that drive major C losses of this ecosystem in Mexico. Also, we evaluated the applicability of the already published above ground biomass (AGB) maps to quantify and allocate changes in C stocks. The results suggest that biomass maps can be used to capture the patterns of AGB distribution and to identify the driving forces of C emissions. The C losses are more related to socioeconomic drivers than biophysical characteristics like topography and climate. Besides, this study shows that published current AGB maps may be used for landscape management, including conservation and restoration areas.

Ecosystem services in different agro-climatic zones in eastern India: impact of land use and land cover change

Land use and land cover (LULC) change have considerable influence on ecosystem services. Assessing change in ecosystem services due to LULC change at different spatial and temporal scales will help to identify suitable management practices for sustaining ecosystem productivity and maintaining the ecological balance. The objective of this study was to investigate variations in ecosystem services in response to LULC change over 27 years in four agro-climatic zones (ACZ) of eastern India using satellite imagery for the year 1989, 1996, 2005, 2011 (Landsat TM) and 2016 (Landsat 8 OLI). The satellite images were classified into six LULC classes, agriculture land, forest, waterbody, wasteland, built-up, and mining area. During the study period (1989 to 2016), forest cover reduced by 5.2%, 13.7%, and 3.6% in Sambalpur, Keonjhar, and Kandhamal districts of Odisha, respectively. In Balasore, agricultural land reduced by 17.2% due to its conversion to built-up land. The value of ecosystem services per unit area followed the order of waterbodies > agricultural land > forests. A different set of indicators, e.g., by explicitly including diversity, could change the rank between these land uses, so the temporal trends within a land use are more important than the absolute values. Total ecosystem services increased by US$ 1296.4 × 10⁵ (50.74%), US$ 1100.7 × 10⁵ (98.52%), US$ 1867 × 10⁵ (61.64%), and US$ 1242.6 × 10⁵ (46.13%) for Sambalpur, Balasore, Kandhamal, and Keonjhar, respectively.

Using satellite data to monitor land-use land-cover change in North-eastern Latvia

Land-use and land-cover change (LULCC), especially those caused by human activities, is one of the most important components of global environmental change (Jessen 3^rd edition: 1-526 2005). In this study the effects of geographic and demographic factors on LULCC are analyzed in northeastern Latvia using official estimates from census and vital statistics data, and using remotely sensed satellite imagery (Landsat Thematic Mapper) acquired from 1992 and 2007. The remote sensing images, elevation data, in-situ ground truth and ground control data (using GPS), census and vital statistics data were processed, integrated, and analyzed in a geographic information system (GIS). Changes in six categories of land-use and land-cover (wetland, water, agriculture, forest, bare field and urban/suburban) were studied to determine their relationship to demographic and geographic factors between 1992 and 2007. Supervised classifications were performed on the Landsat images. Analysis of land cover change based on “change-to” categories between the 1992 and 2007 images revealed that changes to forest were the most common type of change (17.1% of pixels), followed by changes to agriculture (8.6%) and the fewest were changes to urban/suburban (0.8%). Integration of population data and land-cover change data revealed key findings: areas near to roads underwent more LULCC and areas far away from Riga underwent less LULCC. Range in elevation was positively correlated with all LULCC categories. Population density was found to be associated with most LULCC categories but the direction of effect was scale dependent. This paper shows how socio-demographic data can be integrated with satellite image data and cartographic data to analyze drivers of LULCC at multiple spatial scales.