Assessing Hydrological Impact of Forested Area Change: A Remote Sensing Case Study

The interaction between precipitation and vegetation plays a significant role in the formation of runoff, and it is still a widely discussed issue in hydrology. The difficulty lies in estimating the degree to which a forest influences runoff generation, especially flood peaks, on the one hand, due to the small amount of information regarding the evolution of the forest area and density, and, on the other hand, the correlations between these indicators and the runoff and precipitation values. The analysis focuses on a small basin in the mountain region of Romania, the upper basin of the Ruscova River located in northwestern Romania. In this river basin, there is no significant anthropic influence, other than the intense deforestation and reforestation actions. Using satellite images captured by Landsat missions 5, 7 and 8 for the period 1985–2019, the forest canopy density vegetation index was extracted. Using a gridded precipitation dataset, a hydrological model was calibrated based on three scenarios to assess the impact of forest vegetation on the runoff. Analysis of the results of these models conducted on scenarios allowed us to deduce a simple equation for estimating the influence of forest area on maximum river flows. The analysis showed that even small differences in the forest surface area exert an influence on the peak flow, varying between −5.28% and 8.09%.

Mapping Above-Ground Carbon Stock of Secondary Peat Swamp Forest Using Forest Canopy Density Model Landsat 8 OLI-TIRS: A Case Study in Central Kalimantan Indonesia

Mapping the above-ground carbon potential by using a non-destructive method has been a serious challenge for researchers in the effort to improve the performance of natural forest management in Indonesia, particularly in the ex-Mega Rice Project (MRP) area in Central Kalimantan Province. Nevertheless, the rapid and dynamic changes in secondary peat swamp forests are currently mapped effectively with the remote sensing technology using the Forest Canopy Density (FCD) model. FCD analysis as done by integrating vegetation index, soil index, temperature index and shadow index of Landsat 8 OLI images. The result was an FCD class map. In each class, parameter measurements were established for seedling, sapling, poles and tree stages. Above-ground carbon stock was calculated using three allometric equations. The results revealed that the values of carbon stock in ±16,147.26 ha dense secondary peat swamp forest, ±1,509.66 ha moderately dense scrub swamp forest, and ±632.07 ha sparse scrub swamp forest were, respectively, 79.28-122.96; 74.06-113.06; and 40.48-63.60 ton/ha. These results show that FCD application could be used to classify forest density effectively and in line with the variety of their attributes such us aboveground biomass and carbon stock potential.

Analisis Komparasi Metode Pemetaan Ekosistem Mangrove Menggunakan Penginderaan Jauh dan Sistem Informasi Geografis

The use of tools and methods in mapping mangrove ecosystem continues to change.Nowday's trend in mapping is to use remote sensing and digital geographic Information system technology. There are several commonly used methods for mapping the mangrove ecosystem, but we should be aware that choosing the right method of analysis will greatly support the quality of research. The research method is literature review from various books and accredited scientific journals. Subsequently conducted analysis of application methods of mapping mangrove ecosystem of various case studies and research needs. Based on research, there are five methods and analysis used i.e.manual interpretation with Mirror stereoscope, NDVI (Normalized Difference Vegetation Index) as the most common analysis for mangrove distribution mapping. Multivariat PCA (Principal Component Analysis), FCD (Forest Canopy Density) model, and copmpare methods to mapping the extensive changes of mangrove ecosystems. Therefore, this article can be an input for the prospective mangrove ecosystem researchers in determining the preciese method of analysis.

Evaluasi Tingkat Kekritisan Hutan Mangrove dengan Menggunakan Teknologi Spasial di Kawasan Pesisir Timur Aceh

Abstrak. Hutan mangrove di pesisir Kota Langsa semakin lama semakin terancam keberadaannya. Penyalahgunaan hutan mangrove yang dilakukan dalam kurun waktu akhir-akir ini telah menimbulkan berbagai kerusakan sehingga menyebabkan tingkat kekritisannya semakin tinggi. Salah satu upaya yang dapat dilakukan untuk mengatasi hal tersebut adalah dengan memanfaatkan teknologi spasial. Teknologi spasial merupakan salah satu media yang penting untuk melakukan perencanaan pembangunan dan pengelolaan sumber daya alam dengan cakupan yang luas. Penelitian ini bertujuan untuk mengetauhi seberapa besar tingkat kekrtitisan hutan mangrove sehingga dapat dilakukan upaya pemulihan bagi hutan mangrove dengan tingkat kekritisan yang tinggi. Kriteria yang digunakan untuk mengetahui tigkat kekrtitisan hutan mangrove yaitu jenis penggunaan lahan, kerapatan tajuk tanaman, dan ketahanan tanah terhadap abrasi. Hasil penelitian menunjukkan hutan mangrove dengan tingkat kekritisan tertinggi terjadi di kawasan pesisir Langsa bagian timur dengan kategori sangat kritis seluas 453,25 Ha atau 42,16 %, sedangkan hutan mangrove yang termasuk kategori kritis seluas 1.108,99 Ha atau 44%, serta yang tegolong ke dalam kategori tidak kritis seluas 2.337,78 Ha atau 56.70%.Critical Level of Mangrove Forest Using Spatial Technology Case Study in Coastal Areas of LangsaAbstract. Mangrove forests in coastal areas of Langsa are increasingly threatened. The misuse of mangrove forests that have been carried out at the end-time period has caused various damage, causing the critical level to be higher. One effort that can be done to overcome this problem is to utilize spatial technology. Spatial technology is one of the important media for carrying out extensive development planning and natural resource management The purpose of this study is to determine the critical level of mangrove forests so that recovery efforts can be done for mangrove forests with highest criticality level. The criteria used to determine the critical level of mangrove forests are the type of land use, forest canopy density, and soil resistance to abrasion. The results showed that the highest critical level of mangrove forest occurred in the eastern coastal areas of Langsa with very critical category is 453.25 ha or 42.16%, mangrove forests included in the critical category is 1,108.99 ha or 44%, and those classified to the non-critical category is 2,337.78 ha or 56.70%.

Application of Forest Canopy Density (FCD) Model for the Hotspot Monitoring of Crown Fire in Tebo, Jambi Province

<p><em>Indonesia is one of the owners of the 9th largest forest area in the world. Forest area in Indonesia reaches 884,950 km². Tebo Regency is a regency in Jambi Province which has a wide forest area of 628,003 Ha. However, this forest area has been reduced due to the conversion of functions of Industrial Plantation Forests (HTI), oil palm plantations, and forest clearing activities for both settlements and plantations which led to the phenomenon of forest and land fires (karhutla). This study aims to get a better knowledge of crowns of fire potential locations in forest areas using remote sensing technology. Remote sensing data used in this study is from the satellite imagery </em><em>of </em><em>Landsat 8 OLI - TIRS in 2019. Remote sensing data is used to produce a Forest Canopy Density (FCD) model that can be overlap</em><em>ped with</em><em> a hotspot location, so the crown fire potential locations will be explored in the forest area of Tebo Regency, Jambi Province. Identification of hotspot patterns in Forest Areas was analyzed using spatial analysis. The results of this study are useful for the government as the information of the hotspot area as the cause of fires in the Forest Region of Tebo Regency Jambi Province.</em></p><strong><em>Keywords</em></strong><em>: Spatial Analysis, Forest Cover Density (FCD), Hotspots, Forest Areas, Remote Sensing</em>