LiDAR with Pulsed Time of Flight

LIDAR data has proved useful in recent years since it gives information such as item height and attributes, statistics over large regions, and it all becomes available by capturing the intensity of backscattered pulses in addition to 3D coordinates. “A LiDAR may generate a 2D angle image as well as a 3D picture containing angle/angle/range information. A LiDAR can directly measure range in each pixel since it controls when light is emitted, allowing it to calculate range based on the time of flight (ToF) to and from the object in a particular pixel. If there is enough signal, a 3D picture can also have grayscale and colour”. Coherent LiDAR can detect velocity quite precisely. Brief descriptions of airborne laser scanning technology [also known as "light detection and ranging" (LIDAR)] and research findings on its application in forest assessment and monitoring are included. Many airborne laser scanning missions are being flown with terrain mapping requirements, leading to data sets that are missing important data for vegetation evaluation. As a result, standards and criteria for airborne laser scanning missions are needed to guarantee that they are used for vegetation measurement and monitoring instead of merely landscape mapping (e.g., delivery of all return data with reflection intensity).

FOREST ASSESSMENT AND ACCOUNTING SOFTWARE

Forestry in Russia is experiencing a great need for digital technologies that can form and generalize existing databases. All participants are interested in the development of digital technologies in forest management, from the end user of forest resources to public authorities in the field of forest relations. At the same time, the modern level of forestry software requires modernization to solve specific problems. The team of the Department of Forestry, Forest Inventory and Forest Inventory of VGFTU has developed a number of automated systems that allow to quickly solve scientific and production problems in the field of forestry, ecology and nature management. The importance and relevance of this work is reflected in the “Strategy for the development of the forestry complex of the Russian Federation for the period up to 2030”.The modularity and scalability of such systems allows the authors to quickly make adjustments to their source code, which allows keeping the software up to date, which meets the modern requirements of the legal framework of the forestry sector.

A Synthesis of Spatial Forest Assessment Studies Using Remote Sensing Data and Techniques in Pakistan

This paper synthesizes research studies on spatial forest assessment and mapping using remote sensing data and techniques in Pakistan. The synthesis states that 73 peer-reviewed research articles were published in the past 28 years (1993–2021). Out of all studies, three were conducted in Azad Jammu & Kashmir, one in Balochistan, three in Gilgit-Baltistan, twelve in Islamabad Capital Territory, thirty-one in Khyber Pakhtunkhwa, six in Punjab, ten in Sindh, and the remaining seven studies were conducted on national/regional scales. This review discusses the remote sensing classification methods, algorithms, published papers' citations, limitations, and challenges of forest mapping in Pakistan. The literature review suggested that the supervised image classification method and maximum likelihood classifier were among the most frequently used image classification and classification algorithms. The review also compared studies before and after the 18th constitutional amendment in Pakistan. Very few studies were conducted before this constitutional amendment, while a steep increase was observed afterward. The image classification accuracies of published papers were also assessed on local, regional, and national scales. The spatial forest assessment and mapping in Pakistan were evaluated only once using active remote sensing data (i.e., SAR). Advanced satellite imageries, the latest tools, and techniques need to be incorporated for forest mapping in Pakistan to facilitate forest stakeholders in managing the forests and undertaking national projects like UN’s REDD+ effectively.

CANOPY COVER ESTIMATION FROM SATELLITE DATA FOR <i>ACACIA MANGIUM</i> PLANTATION BASAY, NEGROS ORIENTAL

Forest assessment and measurement can be costly, laborious and time-consuming when done manually. Remote Sensing aids by providing data of sufficient accuracy for large tracts of forest lands in the form of maps. These data can then assist in decision- making for better forest management. This study estimated canopy cover, a primary forest measurement parameter, using remotely- sensed data. Satellite images such as Planetscope and WorldView were used to estimate canopy cover. The results were then compared to measurements obtained from a manual inventory – in this case, of an Acacia mangium plantation. The manual inventory was conducted in a National Greening Program (NGP) site in Basay, Negros Oriental. Field inventory involved a Static Global Navigation Satellite System (GNSS) survey and a Total Station survey to get the accurate location of trees present in the plot. Diameter- at- breast was measured for all trees. Tree height and crown diameter were measured for at least 10 percent of all trees in the plot.